Update metrics

backend/app/services/leaderboard.py

@@ -104,32 +104,67 @@ class LeaderboardService:
             
             # Create unique ID combining model name, precision, sha and chat template status
             unique_id = f"{data.get('fullname', 'Unknown')}_{data.get('Precision', 'Unknown')}_{data.get('Model sha', 'Unknown')}_{str(data.get('Chat Template', False))}"
-            
+
             evaluations = {
-                "multifin": {
-                    "name": "MultiFin",
-                    "value": data.get("MultiFin Raw", 0),
-                    "normalized_score": data.get("MultiFin", 0)
+                "bc5cdr_chemical": {
+                    "name": "BC5CDR-chemical",
+                    "value": data.get("BC5CDR-chemical", 0),
+                    "normalized_score": data.get("BC5CDR-chemical", 0),
+                },
+                "ncbi_disease": {
+                    "name": "NCBI Disease",
+                    "value": data.get("NCBI Disease", 0),
+                    "normalized_score": data.get("NCBI Disease", 0),
+                },
+                "chemprot": {
+                    "name": "ChemProt",
+                    "value": data.get("ChemProt", 0),
+                    "normalized_score": data.get("ChemProt", 0),
+                },
+                "ddi2013": {
+                    "name": "DDI2013",
+                    "value": data.get("DDI2013", 0),
+                    "normalized_score": data.get("DDI2013", 0),
+                },
+                "hoc": {
+                    "name": "HoC",
+                    "value": data.get("HoC", 0),
+                    "normalized_score": data.get("HoC", 0),
+                },
+                "litcovid": {
+                    "name": "LitCovid",
+                    "value": data.get("LitCovid", 0),
+                    "normalized_score": data.get("LitCovid", 0),
+                },
+                "medqa": {
+                    "name": "MedQA (5-Option)",
+                    "value": data.get("MedQA (5-Option)", 0),
+                    "normalized_score": data.get("MedQA (5-Option)", 0),
+                },
+                "pubmedqa": {
+                    "name": "PubMedQA",
+                    "value": data.get("PubMedQA", 0),
+                    "normalized_score": data.get("PubMedQA", 0),
                 },
-                "qa": {
-                    "name": "QA",
-                    "value": data.get("QA Raw", 0),
-                    "normalized_score": data.get("QA", 0)
+                "pubmed": {
+                    "name": "PubMed",
+                    "value": data.get("PubMed", 0),
+                    "normalized_score": data.get("PubMed", 0),
                 },
-                "fns": {
-                    "name": "FNS",
-                    "value": data.get("FNS Raw", 0),
-                    "normalized_score": data.get("FNS", 0)
+                "ms2": {
+                    "name": "MS^2",
+                    "value": data.get("MS^2", 0),
+                    "normalized_score": data.get("MS^2", 0),
                 },
-                "finnum": {
-                    "name": "FinNum",
-                    "value": data.get("FinNum Raw", 0),
-                    "normalized_score": data.get("FinNum", 0)
+                "cochrane_pls": {
+                    "name": "Cochrane PLS",
+                    "value": data.get("Cochrane PLS", 0),
+                    "normalized_score": data.get("Cochrane PLS", 0),
                 },
-                "fintext": {
-                    "name": "FinText",
-                    "value": data.get("FinText Raw", 0),
-                    "normalized_score": data.get("FinText", 0)
+                "plos": {
+                    "name": "PLOS",
+                    "value": data.get("PLOS", 0),
+                    "normalized_score": data.get("PLOS", 0),
                 },
             }
 

frontend/src/pages/LeaderboardPage/components/Leaderboard/constants/defaults.js

@@ -98,158 +98,200 @@ const COLUMN_SIZES = {
 
 // Column definitions with organized structure
 const COLUMNS = {
-  FIXED: {
-    rank: {
-      group: "fixed",
-      size: COLUMN_SIZES.RANK,
-      defaultVisible: true,
-      label: "Rank",
+    FIXED: {
+        rank: {
+            group: "fixed",
+            size: COLUMN_SIZES.RANK,
+            defaultVisible: true,
+            label: "Rank",
+        },
+        "model.type_icon": {
+            group: "fixed",
+            size: COLUMN_SIZES.TYPE_ICON,
+            defaultVisible: true,
+            label: "Type",
+        },
+        id: {
+            group: "fixed",
+            size: COLUMN_SIZES.MODEL,
+            defaultVisible: true,
+            label: "Model",
+        },
+        "model.average_score": {
+            group: "fixed",
+            size: COLUMN_SIZES.AVERAGE_SCORE,
+            defaultVisible: true,
+            label: "Average Score",
+        },
     },
-    "model.type_icon": {
-      group: "fixed",
-      size: COLUMN_SIZES.TYPE_ICON,
-      defaultVisible: true,
-      label: "Type",
+    EVALUATION: {
+        "evaluations.bc5cdr_chemical.normalized_score": {
+            group: "evaluation",
+            size: COLUMN_SIZES.BENCHMARK,
+            defaultVisible: true,
+            label: "BC5CDR-chemical",
+        },
+        "evaluations.ncbi_disease.normalized_score": {
+            group: "evaluation",
+            size: COLUMN_SIZES.BENCHMARK,
+            defaultVisible: true,
+            label: "NCBI Disease",
+        },
+        "evaluations.chemprot.normalized_score": {
+            group: "evaluation",
+            size: COLUMN_SIZES.BENCHMARK,
+            defaultVisible: true,
+            label: "ChemProt",
+        },
+        "evaluations.ddi2013.normalized_score": {
+            group: "evaluation",
+            size: COLUMN_SIZES.BENCHMARK,
+            defaultVisible: true,
+            label: "DDI2013",
+        },
+        "evaluations.hoc.normalized_score": {
+            group: "evaluation",
+            size: COLUMN_SIZES.BENCHMARK,
+            defaultVisible: true,
+            label: "HoC",
+        },
+        "evaluations.litcovid.normalized_score": {
+            group: "evaluation",
+            size: COLUMN_SIZES.BENCHMARK,
+            defaultVisible: true,
+            label: "LitCovid",
+        },
+        "evaluations.medqa.normalized_score": {
+            group: "evaluation",
+            size: COLUMN_SIZES.BENCHMARK,
+            defaultVisible: true,
+            label: "MedQA (5-Option)",
+        },
+        "evaluations.pubmedqa.normalized_score": {
+            group: "evaluation",
+            size: COLUMN_SIZES.BENCHMARK,
+            defaultVisible: true,
+            label: "PubMedQA",
+        },
+        "evaluations.pubmed.normalized_score": {
+            group: "evaluation",
+            size: COLUMN_SIZES.BENCHMARK,
+            defaultVisible: true,
+            label: "PubMed",
+        },
+        "evaluations.ms2.normalized_score": {
+            group: "evaluation",
+            size: COLUMN_SIZES.BENCHMARK,
+            defaultVisible: true,
+            label: "MS^2",
+        },
+        "evaluations.cochrane_pls.normalized_score": {
+            group: "evaluation",
+            size: COLUMN_SIZES.BENCHMARK,
+            defaultVisible: true,
+            label: "Cochrane PLS",
+        },
+        "evaluations.plos.normalized_score": {
+            group: "evaluation",
+            size: COLUMN_SIZES.BENCHMARK,
+            defaultVisible: true,
+            label: "PLOS",
+        },
     },
-    id: {
-      group: "fixed",
-      size: COLUMN_SIZES.MODEL,
-      defaultVisible: true,
-      label: "Model",
+    MODEL_INFO: {
+        "metadata.co2_cost": {
+            group: "model_info",
+            size: COLUMN_SIZES.CO2_COST,
+            defaultVisible: true,
+            label: "CO₂ Cost (kg)",
+        },
+        "metadata.hub_hearts": {
+            group: "model_info",
+            size: COLUMN_SIZES.HUB_HEARTS,
+            defaultVisible: false,
+            label: "Hub ❤️",
+        },
+        "model.architecture": {
+            group: "model_info",
+            size: COLUMN_SIZES.ARCHITECTURE,
+            defaultVisible: false,
+            label: "Architecture",
+        },
+        "model.precision": {
+            group: "model_info",
+            size: COLUMN_SIZES.PRECISION,
+            defaultVisible: false,
+            label: "Precision",
+        },
+        "metadata.params_billions": {
+            group: "model_info",
+            size: COLUMN_SIZES.PARAMS,
+            defaultVisible: false,
+            label: "Parameters (B)",
+        },
+        "metadata.hub_license": {
+            group: "model_info",
+            size: COLUMN_SIZES.LICENSE,
+            defaultVisible: false,
+            label: "License",
+        },
+        "model.has_chat_template": {
+            group: "model_info",
+            size: COLUMN_SIZES.CHAT_TEMPLATE,
+            defaultVisible: false,
+            label: "Chat Template",
+        },
     },
-    "model.average_score": {
-      group: "fixed",
-      size: COLUMN_SIZES.AVERAGE_SCORE,
-      defaultVisible: true,
-      label: "Average Score",
+    ADDITIONAL_INFO: {
+        "metadata.upload_date": {
+            group: "additional_info",
+            size: COLUMN_SIZES.UPLOAD_DATE,
+            defaultVisible: false,
+            label: "Upload Date",
+        },
+        "metadata.submission_date": {
+            group: "additional_info",
+            size: COLUMN_SIZES.SUBMISSION_DATE,
+            defaultVisible: false,
+            label: "Submission Date",
+        },
+        "metadata.generation": {
+            group: "additional_info",
+            size: COLUMN_SIZES.GENERATION,
+            defaultVisible: false,
+            label: "Generation",
+        },
+        "metadata.base_model": {
+            group: "additional_info",
+            size: COLUMN_SIZES.BASE_MODEL,
+            defaultVisible: false,
+            label: "Base Model",
+        },
+        "features.is_not_available_on_hub": {
+            group: "additional_info",
+            size: COLUMN_SIZES.HUB_AVAILABILITY,
+            defaultVisible: false,
+            label: "Hub Availability",
+        },
+        "features.is_highlighted_by_maintainer": {
+            group: "additional_info",
+            size: COLUMN_SIZES.OFFICIAL_PROVIDER,
+            defaultVisible: false,
+            label: "Only Official Providers",
+        },
+        "features.is_moe": {
+            group: "additional_info",
+            size: COLUMN_SIZES.MOE,
+            defaultVisible: false,
+            label: "Mixture of Experts",
+        },
+        "features.is_flagged": {
+            group: "additional_info",
+            size: COLUMN_SIZES.FLAG_STATUS,
+            defaultVisible: false,
+            label: "Flag Status",
+        },
     },
-  },
-  EVALUATION: {
-    "evaluations.multifin.normalized_score": {
-      group: "evaluation",
-      size: COLUMN_SIZES.BENCHMARK,
-      defaultVisible: true,
-      label: "MultiFin",
-    },
-    "evaluations.qa.normalized_score": {
-      group: "evaluation",
-      size: COLUMN_SIZES.BENCHMARK,
-      defaultVisible: true,
-      label: "QA",
-    },
-    "evaluations.fns.normalized_score": {
-      group: "evaluation",
-      size: COLUMN_SIZES.BENCHMARK,
-      defaultVisible: true,
-      label: "FNS",
-    },
-    "evaluations.finnum.normalized_score": {
-      group: "evaluation",
-      size: COLUMN_SIZES.BENCHMARK,
-      defaultVisible: true,
-      label: "FinNum",
-    },
-    "evaluations.fintext.normalized_score": {
-      group: "evaluation",
-      size: COLUMN_SIZES.BENCHMARK,
-      defaultVisible: true,
-      label: "FinText",
-    },
-  },
-  MODEL_INFO: {
-    "metadata.co2_cost": {
-      group: "model_info",
-      size: COLUMN_SIZES.CO2_COST,
-      defaultVisible: true,
-      label: "CO₂ Cost (kg)",
-    },
-    "metadata.hub_hearts": {
-      group: "model_info",
-      size: COLUMN_SIZES.HUB_HEARTS,
-      defaultVisible: false,
-      label: "Hub ❤️",
-    },
-    "model.architecture": {
-      group: "model_info",
-      size: COLUMN_SIZES.ARCHITECTURE,
-      defaultVisible: false,
-      label: "Architecture",
-    },
-    "model.precision": {
-      group: "model_info",
-      size: COLUMN_SIZES.PRECISION,
-      defaultVisible: false,
-      label: "Precision",
-    },
-    "metadata.params_billions": {
-      group: "model_info",
-      size: COLUMN_SIZES.PARAMS,
-      defaultVisible: false,
-      label: "Parameters (B)",
-    },
-    "metadata.hub_license": {
-      group: "model_info",
-      size: COLUMN_SIZES.LICENSE,
-      defaultVisible: false,
-      label: "License",
-    },
-    "model.has_chat_template": {
-      group: "model_info",
-      size: COLUMN_SIZES.CHAT_TEMPLATE,
-      defaultVisible: false,
-      label: "Chat Template",
-    },
-  },
-  ADDITIONAL_INFO: {
-    "metadata.upload_date": {
-      group: "additional_info",
-      size: COLUMN_SIZES.UPLOAD_DATE,
-      defaultVisible: false,
-      label: "Upload Date",
-    },
-    "metadata.submission_date": {
-      group: "additional_info",
-      size: COLUMN_SIZES.SUBMISSION_DATE,
-      defaultVisible: false,
-      label: "Submission Date",
-    },
-    "metadata.generation": {
-      group: "additional_info",
-      size: COLUMN_SIZES.GENERATION,
-      defaultVisible: false,
-      label: "Generation",
-    },
-    "metadata.base_model": {
-      group: "additional_info",
-      size: COLUMN_SIZES.BASE_MODEL,
-      defaultVisible: false,
-      label: "Base Model",
-    },
-    "features.is_not_available_on_hub": {
-      group: "additional_info",
-      size: COLUMN_SIZES.HUB_AVAILABILITY,
-      defaultVisible: false,
-      label: "Hub Availability",
-    },
-    "features.is_highlighted_by_maintainer": {
-      group: "additional_info",
-      size: COLUMN_SIZES.OFFICIAL_PROVIDER,
-      defaultVisible: false,
-      label: "Only Official Providers",
-    },
-    "features.is_moe": {
-      group: "additional_info",
-      size: COLUMN_SIZES.MOE,
-      defaultVisible: false,
-      label: "Mixture of Experts",
-    },
-    "features.is_flagged": {
-      group: "additional_info",
-      size: COLUMN_SIZES.FLAG_STATUS,
-      defaultVisible: false,
-      label: "Flag Status",
-    },
-  },
 };
 
 // Combine all columns for backward compatibility

frontend/src/pages/LeaderboardPage/components/Leaderboard/constants/tooltips.js

@@ -29,209 +29,289 @@ const createTooltipContent = (title, items) => (
 );
 
 export const COLUMN_TOOLTIPS = {
-  AVERAGE: createTooltipContent("Average score across all benchmarks:", [
-    {
-      label: "Calculation",
-      description: "Weighted average of normalized scores from all benchmarks",
-      subItems: [
-        "Each benchmark is normalized to a 0-100 scale",
-        "All normalised benchmarks are then averaged together",
-      ],
-    },
-  ]),
+    AVERAGE: createTooltipContent("Average score across all benchmarks:", [
+        {
+            label: "Calculation",
+            description:
+                "Weighted average of normalized scores from all benchmarks",
+            subItems: [
+                "Each benchmark is normalized to a 0-100 scale",
+                "All normalised benchmarks are then averaged together",
+            ],
+        },
+    ]),
 
-  MULTIFIN: createTooltipContent("Multilingual Financial NLP (MultiFin):", [
-    {
-      label: "Purpose",
-      description:
-        "Tests model's ability to understand real-world financial article headlines",
-      subItems: ["Language Understanding", "Topic Classification"],
-    },
-    {
-      label: "Scoring: ACC Norm",
-      description: "Was the correct choice selected among the options.",
-    },
-  ]),
+    BC5CDR_CHEMICAL: createTooltipContent("Placeholder", [
+        {
+            label: "Purpose",
+            description: "Placeholder",
+            subItems: ["Placeholder", "Placeholder"],
+        },
+        {
+            label: "Scoring: Placeholder",
+            description: "Placeholder",
+        },
+    ]),
 
-  QA: createTooltipContent("Greek Financial Question Answering (QA):", [
-    {
-      label: "Purpose",
-      description:
-        "Tests model's ability to understand real-world Greek financial exam questions",
-      subItems: ["Language Understanding", "Question Answering"],
-    },
-    {
-      label: "Scoring: ACC Norm",
-      description: "Was the correct choice selected among the options.",
-    },
-  ]),
+    NCBI_DISEASE: createTooltipContent("Placeholder", [
+        {
+            label: "Purpose",
+            description: "Placeholder",
+            subItems: ["Placeholder", "Placeholder"],
+        },
+        {
+            label: "Scoring: Placeholder",
+            description: "Placeholder",
+        },
+    ]),
 
-  FNS: createTooltipContent("Financial Narrative Summarization (FNS):", [
-    {
-      label: "Purpose",
-      description:
-        "Tests model's ability to summarize real-world financial annual reports",
-      subItems: ["Language Understanding", "Abstractive Summarization"],
-    },
-    {
-      label: "Scoring: Rouge1",
-      description: "Was the overlap of unigrams (each word) between the predicted and reference summaries.",
-    },
-  ]),
+    CHEMPROT: createTooltipContent("Placeholder", [
+        {
+            label: "Purpose",
+            description: "Placeholder",
+            subItems: ["Placeholder", "Placeholder"],
+        },
+        {
+            label: "Scoring: Placeholder",
+            description: "Placeholder",
+        },
+    ]),
 
-  FinNum: createTooltipContent("Financial Number Entity Recognition (FinNum):", [
-    {
-      label: "Purpose",
-      description:
-        "Tests model's ability to recognize numbers from financial texts",
-      subItems: ["Language Understanding", "Named Entity Recognition"],
-    },
-    {
-      label: "Scoring: Rouge1",
-      description: "Was the overlap of unigrams (each word) between the predicted and reference summaries.",
-    },
-  ]),
+    DDI2013: createTooltipContent("Placeholder", [
+        {
+            label: "Purpose",
+            description: "Placeholder",
+            subItems: ["Placeholder", "Placeholder"],
+        },
+        {
+            label: "Scoring: Placeholder",
+            description: "Placeholder",
+        },
+    ]),
 
-  FinText: createTooltipContent("Financial Named Entity Recognition (FinText):", [
-    {
-      label: "Purpose",
-      description:
-        "Tests model's ability to recognize financial entities, i.e, person, location, and organization",
-      subItems: ["Language Understanding", "Named Entity Recognition"],
-    },
-    {
-      label: "Scoring: Rouge1",
-      description: "Was the overlap of unigrams (each word) between the predicted and reference summaries.",
-    },
-  ]),
+    HOC: createTooltipContent("Placeholder", [
+        {
+            label: "Purpose",
+            description: "Placeholder",
+            subItems: ["Placeholder", "Placeholder"],
+        },
+        {
+            label: "Scoring: Placeholder",
+            description: "Placeholder",
+        },
+    ]),
 
-  ARCHITECTURE: createTooltipContent("Model Architecture Information:", [
-    {
-      label: "Definition",
-      description: "The fundamental structure and design of the model",
-      subItems: [
-        "Pretrained: Foundational models, initially trained on large datasets without task-specific tuning, serving as a versatile base for further development.",
-        "Continuously Pretrained: Base models trained with a data mix evolving as the model is trained, with the addition of specialized data during the last training steps.",
-        "Fine-tuned: Base models, fine-tuned on specialised domain data (legal, medical, ...), and optimized for particular tasks.",
-        "Chat: Models fine-tuned with IFT, RLHF, DPO, and other techniques, to handle conversational contexts effectively.",
-        "Merged: Combining multiple models through weights averaging or similar methods.",
-        "Multimodal: Models which can handle several modalities (text & image/audio/video/...). We only evaluate the text capabilities.",
-      ],
-    },
-    {
-      label: "Impact",
-      description: "How architecture affects model capabilities",
-      subItems: [
-        "Base models are expected to perform less well on instruction following evaluations, like IFEval.",
-        "Fine-tuned and chat models can be more verbose and more chatty than base models.",
-        "Merged models tend to exhibit good performance on benchmarks, which do not translate to real-world situations.",
-      ],
-    },
-  ]),
+    LITCOVID: createTooltipContent("Placeholder", [
+        {
+            label: "Purpose",
+            description: "Placeholder",
+            subItems: ["Placeholder", "Placeholder"],
+        },
+        {
+            label: "Scoring: Placeholder",
+            description: "Placeholder",
+        },
+    ]),
 
-  PRECISION: createTooltipContent("Numerical Precision Format:", [
-    {
-      label: "Overview",
-      description:
-        "Data format used to store model weights and perform computations",
-      subItems: [
-        "bfloat16: Half precision (Brain Float format), good for stability",
-        "float16: Half precision",
-        "8bit/4bit: Quantized formats, for efficiency",
-        "GPTQ/AWQ: Quantized methods",
-      ],
-    },
-    {
-      label: "Impact",
-      description: "How precision affects model deployment",
-      subItems: [
-        "Higher precision = better accuracy but more memory usage",
-        "Lower precision = faster inference and smaller size",
-        "Trade-off between model quality and resource usage",
-      ],
-    },
-  ]),
+    MEDQA: createTooltipContent("Placeholder", [
+        {
+            label: "Purpose",
+            description: "Placeholder",
+            subItems: ["Placeholder", "Placeholder"],
+        },
+        {
+            label: "Scoring: Placeholder",
+            description: "Placeholder",
+        },
+    ]),
 
-  FLAGS: createTooltipContent("Model Flags and Special Features:", [
-    {
-      label: "Filters",
-      subItems: [
-        "Mixture of Expert: Uses a MoE architecture",
-        "Merged models: Created by averaging other models",
-        "Contaminated: Flagged by users from the community for (possibly accidental) cheating",
-        "Unavailable: No longer on the hub (private, deleted) or missing a license tag",
-      ],
-    },
-    {
-      label: "Purpose",
-      description: "Why do people want to hide these models?",
-      subItems: [
-        "Mixture of Experts: These models can be too parameter heavy",
-        "Merged models: Performance on benchmarks tend to be inflated compared to real life usage",
-        "Contaminated: Performance on benchmarks is inflated and not reflecting real life usage",
-      ],
-    },
-  ]),
+    PUBMEDQA: createTooltipContent("Placeholder", [
+        {
+            label: "Purpose",
+            description: "Placeholder",
+            subItems: ["Placeholder", "Placeholder"],
+        },
+        {
+            label: "Scoring: Placeholder",
+            description: "Placeholder",
+        },
+    ]),
 
-  PARAMETERS: createTooltipContent("Model Parameters:", [
-    {
-      label: "Measurement",
-      description: "Total number of trainable parameters in billions",
-      subItems: [
-        "Indicates model capacity and complexity",
-        "Correlates with computational requirements",
-        "Influences memory usage and inference speed",
-      ],
-    },
-  ]),
+    PUBMED: createTooltipContent("Placeholder", [
+        {
+            label: "Purpose",
+            description: "Placeholder",
+            subItems: ["Placeholder", "Placeholder"],
+        },
+        {
+            label: "Scoring: Placeholder",
+            description: "Placeholder",
+        },
+    ]),
 
-  LICENSE: createTooltipContent("Model License Information:", [
-    {
-      label: "Importance",
-      description: "Legal terms governing model usage and distribution",
-      subItems: [
-        "Commercial vs non-commercial use",
-        "Attribution requirements",
-        "Modification and redistribution rights",
-        "Liability and warranty terms",
-      ],
-    },
-  ]),
+    MS2: createTooltipContent("Placeholder", [
+        {
+            label: "Purpose",
+            description: "Placeholder",
+            subItems: ["Placeholder", "Placeholder"],
+        },
+        {
+            label: "Scoring: Placeholder",
+            description: "Placeholder",
+        },
+    ]),
 
-  CO2_COST: createTooltipContent("Carbon Dioxide Emissions:", [
-    {
-      label: "What is it?",
-      description: "CO₂ emissions of the model evaluation ",
-      subItems: [
-        "Only focuses on model inference for our specific setup",
-        "Considers data center location and energy mix",
-        "Allows equivalent comparision of models on our use case",
-      ],
-    },
-    {
-      label: "Why it matters",
-      description: "Environmental impact of AI model training",
-      subItems: [
-        "Large models can have significant carbon footprints",
-        "Helps make informed choices about model selection",
-      ],
-    },
-    {
-      label: "Learn more",
-      description:
-        "For detailed information about our CO₂ calculation methodology, visit:",
-      subItems: [
-        <a
-          href="https://huggingface.co/docs/leaderboards/open_llm_leaderboard/emissions"
-          target="_blank"
-          rel="noopener noreferrer"
-          style={{ color: "#90caf9" }}
-        >
-          Carbon Emissions Documentation ↗
-        </a>,
-      ],
-    },
-  ]),
+    COCHRANE_PLS: createTooltipContent("Placeholder", [
+        {
+            label: "Purpose",
+            description: "Placeholder",
+            subItems: ["Placeholder", "Placeholder"],
+        },
+        {
+            label: "Scoring: Placeholder",
+            description: "Placeholder",
+        },
+    ]),
+
+    PLOS: createTooltipContent("Placeholder", [
+        {
+            label: "Purpose",
+            description: "Placeholder",
+            subItems: ["Placeholder", "Placeholder"],
+        },
+        {
+            label: "Scoring: Placeholder",
+            description: "Placeholder",
+        },
+    ]),
+
+    ARCHITECTURE: createTooltipContent("Model Architecture Information:", [
+        {
+            label: "Definition",
+            description: "The fundamental structure and design of the model",
+            subItems: [
+                "Pretrained: Foundational models, initially trained on large datasets without task-specific tuning, serving as a versatile base for further development.",
+                "Continuously Pretrained: Base models trained with a data mix evolving as the model is trained, with the addition of specialized data during the last training steps.",
+                "Fine-tuned: Base models, fine-tuned on specialised domain data (legal, medical, ...), and optimized for particular tasks.",
+                "Chat: Models fine-tuned with IFT, RLHF, DPO, and other techniques, to handle conversational contexts effectively.",
+                "Merged: Combining multiple models through weights averaging or similar methods.",
+                "Multimodal: Models which can handle several modalities (text & image/audio/video/...). We only evaluate the text capabilities.",
+            ],
+        },
+        {
+            label: "Impact",
+            description: "How architecture affects model capabilities",
+            subItems: [
+                "Base models are expected to perform less well on instruction following evaluations, like IFEval.",
+                "Fine-tuned and chat models can be more verbose and more chatty than base models.",
+                "Merged models tend to exhibit good performance on benchmarks, which do not translate to real-world situations.",
+            ],
+        },
+    ]),
+
+    PRECISION: createTooltipContent("Numerical Precision Format:", [
+        {
+            label: "Overview",
+            description:
+                "Data format used to store model weights and perform computations",
+            subItems: [
+                "bfloat16: Half precision (Brain Float format), good for stability",
+                "float16: Half precision",
+                "8bit/4bit: Quantized formats, for efficiency",
+                "GPTQ/AWQ: Quantized methods",
+            ],
+        },
+        {
+            label: "Impact",
+            description: "How precision affects model deployment",
+            subItems: [
+                "Higher precision = better accuracy but more memory usage",
+                "Lower precision = faster inference and smaller size",
+                "Trade-off between model quality and resource usage",
+            ],
+        },
+    ]),
+
+    FLAGS: createTooltipContent("Model Flags and Special Features:", [
+        {
+            label: "Filters",
+            subItems: [
+                "Mixture of Expert: Uses a MoE architecture",
+                "Merged models: Created by averaging other models",
+                "Contaminated: Flagged by users from the community for (possibly accidental) cheating",
+                "Unavailable: No longer on the hub (private, deleted) or missing a license tag",
+            ],
+        },
+        {
+            label: "Purpose",
+            description: "Why do people want to hide these models?",
+            subItems: [
+                "Mixture of Experts: These models can be too parameter heavy",
+                "Merged models: Performance on benchmarks tend to be inflated compared to real life usage",
+                "Contaminated: Performance on benchmarks is inflated and not reflecting real life usage",
+            ],
+        },
+    ]),
+
+    PARAMETERS: createTooltipContent("Model Parameters:", [
+        {
+            label: "Measurement",
+            description: "Total number of trainable parameters in billions",
+            subItems: [
+                "Indicates model capacity and complexity",
+                "Correlates with computational requirements",
+                "Influences memory usage and inference speed",
+            ],
+        },
+    ]),
+
+    LICENSE: createTooltipContent("Model License Information:", [
+        {
+            label: "Importance",
+            description: "Legal terms governing model usage and distribution",
+            subItems: [
+                "Commercial vs non-commercial use",
+                "Attribution requirements",
+                "Modification and redistribution rights",
+                "Liability and warranty terms",
+            ],
+        },
+    ]),
+
+    CO2_COST: createTooltipContent("Carbon Dioxide Emissions:", [
+        {
+            label: "What is it?",
+            description: "CO₂ emissions of the model evaluation ",
+            subItems: [
+                "Only focuses on model inference for our specific setup",
+                "Considers data center location and energy mix",
+                "Allows equivalent comparision of models on our use case",
+            ],
+        },
+        {
+            label: "Why it matters",
+            description: "Environmental impact of AI model training",
+            subItems: [
+                "Large models can have significant carbon footprints",
+                "Helps make informed choices about model selection",
+            ],
+        },
+        {
+            label: "Learn more",
+            description:
+                "For detailed information about our CO₂ calculation methodology, visit:",
+            subItems: [
+                <a
+                    href="https://huggingface.co/docs/leaderboards/open_llm_leaderboard/emissions"
+                    target="_blank"
+                    rel="noopener noreferrer"
+                    style={{ color: "#90caf9" }}
+                >
+                    Carbon Emissions Documentation ↗
+                </a>,
+            ],
+        },
+    ]),
 };
 
 export const UI_TOOLTIPS = {

frontend/src/pages/LeaderboardPage/components/Leaderboard/utils/columnUtils.js

@@ -451,614 +451,757 @@ export const createColumns = (
   onTogglePin,
   hasPinnedRows = false
 ) => {
-  // Ajuster les tailles des colonnes en fonction de la présence de lignes épinglées
-  const getColumnSize = (defaultSize) =>
-    hasPinnedRows ? "auto" : `${defaultSize}px`;
+    // Ajuster les tailles des colonnes en fonction de la présence de lignes épinglées
+    const getColumnSize = (defaultSize) =>
+        hasPinnedRows ? "auto" : `${defaultSize}px`;
 
-  const baseColumns = [
-    {
-      accessorKey: "isPinned",
-      header: () => null,
-      cell: ({ row }) => (
-        <Box
-          sx={{
-            display: "flex",
-            alignItems: "center",
-            justifyContent: "center",
-            height: "100%",
-          }}
-        >
-          <IconButton
-            size="small"
-            onClick={(e) => {
-              e.stopPropagation();
-              e.preventDefault();
-              onTogglePin(row.original.id);
-            }}
-            sx={{
-              padding: 0.5,
-              color: row.original.isPinned ? "primary.main" : "grey.400",
-              "&:hover": {
-                color: "primary.main",
-              },
-            }}
-          >
-            {row.original.isPinned ? (
-              <PushPinIcon fontSize="small" />
-            ) : (
-              <PushPinOutlinedIcon fontSize="small" />
-            )}
-          </IconButton>
-        </Box>
-      ),
-      enableSorting: false,
-      size: getColumnSize(40),
-    },
-    {
-      accessorKey: "rank",
-      header: createHeaderCell("Rank"),
-      cell: ({ row }) => {
-        const rank =
-          rankingMode === "static"
-            ? row.original.static_rank
-            : row.original.dynamic_rank;
+    const baseColumns = [
+        {
+            accessorKey: "isPinned",
+            header: () => null,
+            cell: ({ row }) => (
+                <Box
+                    sx={{
+                        display: "flex",
+                        alignItems: "center",
+                        justifyContent: "center",
+                        height: "100%",
+                    }}
+                >
+                    <IconButton
+                        size="small"
+                        onClick={(e) => {
+                            e.stopPropagation();
+                            e.preventDefault();
+                            onTogglePin(row.original.id);
+                        }}
+                        sx={{
+                            padding: 0.5,
+                            color: row.original.isPinned
+                                ? "primary.main"
+                                : "grey.400",
+                            "&:hover": {
+                                color: "primary.main",
+                            },
+                        }}
+                    >
+                        {row.original.isPinned ? (
+                            <PushPinIcon fontSize="small" />
+                        ) : (
+                            <PushPinOutlinedIcon fontSize="small" />
+                        )}
+                    </IconButton>
+                </Box>
+            ),
+            enableSorting: false,
+            size: getColumnSize(40),
+        },
+        {
+            accessorKey: "rank",
+            header: createHeaderCell("Rank"),
+            cell: ({ row }) => {
+                const rank =
+                    rankingMode === "static"
+                        ? row.original.static_rank
+                        : row.original.dynamic_rank;
 
-        return (
-          <RankIndicator
-            rank={rank}
-            previousRank={row.original.previous_rank}
-            mode="static"
-          />
-        );
-      },
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["rank"],
-    },
-    {
-      id: "model_type",
-      accessorFn: (row) => row.model.type,
-      header: createHeaderCell("Type"),
-      sortingFn: typeColumnSort,
-      cell: ({ row }) => (
-        <Box
-          sx={{
-            display: "flex",
-            alignItems: "center",
-            justifyContent: "center",
-            width: "100%",
-          }}
-        >
-          <Tooltip title={row.original.model.type}>
-            <Typography
-              sx={{
-                fontSize: "1.2rem",
-                cursor: "help",
-                lineHeight: 1,
-                fontFamily:
-                  '"Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji", sans-serif',
-              }}
-            >
-              {getModelTypeIcon(row.original.model.type)}
-            </Typography>
-          </Tooltip>
-        </Box>
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.type_icon"],
-    },
-    {
-      accessorKey: "id",
-      header: createModelHeader(totalModels),
-      cell: ({ row }) => {
-        const textSearch = extractTextSearch(searchValue);
-        const modelName = row.original.model.name;
+                return (
+                    <RankIndicator
+                        rank={rank}
+                        previousRank={row.original.previous_rank}
+                        mode="static"
+                    />
+                );
+            },
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["rank"],
+        },
+        {
+            id: "model_type",
+            accessorFn: (row) => row.model.type,
+            header: createHeaderCell("Type"),
+            sortingFn: typeColumnSort,
+            cell: ({ row }) => (
+                <Box
+                    sx={{
+                        display: "flex",
+                        alignItems: "center",
+                        justifyContent: "center",
+                        width: "100%",
+                    }}
+                >
+                    <Tooltip title={row.original.model.type}>
+                        <Typography
+                            sx={{
+                                fontSize: "1.2rem",
+                                cursor: "help",
+                                lineHeight: 1,
+                                fontFamily:
+                                    '"Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji", sans-serif',
+                            }}
+                        >
+                            {getModelTypeIcon(row.original.model.type)}
+                        </Typography>
+                    </Tooltip>
+                </Box>
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.type_icon"],
+        },
+        {
+            accessorKey: "id",
+            header: createModelHeader(totalModels),
+            cell: ({ row }) => {
+                const textSearch = extractTextSearch(searchValue);
+                const modelName = row.original.model.name;
 
-        return (
-          <Box
-            sx={{
-              width: "100%",
-              display: "flex",
-              alignItems: "center",
-              gap: 1,
-            }}
-          >
-            <Box
-              sx={{
-                display: "flex",
-                alignItems: "center",
-                gap: 1,
-                minWidth: 0,
-                flex: 1,
-              }}
-            >
-              <Link
-                href={`https://huggingface.co/${modelName}`}
-                target="_blank"
-                rel="noopener noreferrer"
-                aria-label={`View ${modelName} on Hugging Face Hub`}
-                title={TABLE_TOOLTIPS.HUB_LINK(modelName)}
-                sx={{
-                  textDecoration: "none",
-                  color: "info.main",
-                  display: "flex",
-                  alignItems: "center",
-                  gap: 0.5,
-                  "&:hover": {
-                    textDecoration: "underline",
-                    color: (theme) =>
-                      theme.palette.mode === "dark"
-                        ? theme.palette.info.light
-                        : theme.palette.info.dark,
-                    "& svg": {
-                      opacity: 0.8,
-                    },
-                  },
-                  overflow: "hidden",
-                  textOverflow: "ellipsis",
-                  whiteSpace: "nowrap",
-                  flex: 1,
-                  minWidth: 0,
-                  fontWeight: row.original.static_rank <= 3 ? 600 : "inherit",
-                }}
-              >
-                <HighlightedText text={modelName} searchValue={textSearch} />
-                <OpenInNewIcon
-                  sx={{
-                    fontSize: "0.75rem",
-                    opacity: 0.6,
-                    transition: "opacity 0.2s ease-in-out",
-                    ml: 0.5,
-                    flexShrink: 0,
-                  }}
-                />
-              </Link>
-              <Link
-                href={getDetailsUrl(modelName)}
-                target="_blank"
-                rel="noopener noreferrer"
-                aria-label={`View detailed evaluation results for ${modelName}`}
-                title={TABLE_TOOLTIPS.EVAL_RESULTS(modelName)}
-                sx={{
-                  textDecoration: "none",
-                  "&:hover": {
-                    textDecoration: "underline",
-                    "& svg": {
-                      color: "text.primary",
-                    },
-                  },
-                  display: "flex",
-                  alignItems: "center",
-                  color: "text.secondary",
-                  flexShrink: 0,
-                  mr: 0,
-                }}
-              >
-                <DatabaseIcon />
-              </Link>
-            </Box>
-          </Box>
-        );
-      },
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["id"],
-    },
-    {
-      accessorKey: "model.average_score",
-      header: createHeaderCell("Average", COLUMN_TOOLTIPS.AVERAGE),
-      cell: ({ row, getValue }) =>
-        createScoreCell(getValue, row, "model.average_score"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.average_score"],
-      meta: {
-        headerStyle: {
-          borderLeft: (theme) =>
-            `2px solid ${alpha(
-              theme.palette.divider,
-              theme.palette.mode === "dark" ? 0.1 : 0.2
-            )}`,
-          borderRight: (theme) =>
-            `2px solid ${alpha(
-              theme.palette.divider,
-              theme.palette.mode === "dark" ? 0.1 : 0.2
-            )}`,
+                return (
+                    <Box
+                        sx={{
+                            width: "100%",
+                            display: "flex",
+                            alignItems: "center",
+                            gap: 1,
+                        }}
+                    >
+                        <Box
+                            sx={{
+                                display: "flex",
+                                alignItems: "center",
+                                gap: 1,
+                                minWidth: 0,
+                                flex: 1,
+                            }}
+                        >
+                            <Link
+                                href={`https://huggingface.co/${modelName}`}
+                                target="_blank"
+                                rel="noopener noreferrer"
+                                aria-label={`View ${modelName} on Hugging Face Hub`}
+                                title={TABLE_TOOLTIPS.HUB_LINK(modelName)}
+                                sx={{
+                                    textDecoration: "none",
+                                    color: "info.main",
+                                    display: "flex",
+                                    alignItems: "center",
+                                    gap: 0.5,
+                                    "&:hover": {
+                                        textDecoration: "underline",
+                                        color: (theme) =>
+                                            theme.palette.mode === "dark"
+                                                ? theme.palette.info.light
+                                                : theme.palette.info.dark,
+                                        "& svg": {
+                                            opacity: 0.8,
+                                        },
+                                    },
+                                    overflow: "hidden",
+                                    textOverflow: "ellipsis",
+                                    whiteSpace: "nowrap",
+                                    flex: 1,
+                                    minWidth: 0,
+                                    fontWeight:
+                                        row.original.static_rank <= 3
+                                            ? 600
+                                            : "inherit",
+                                }}
+                            >
+                                <HighlightedText
+                                    text={modelName}
+                                    searchValue={textSearch}
+                                />
+                                <OpenInNewIcon
+                                    sx={{
+                                        fontSize: "0.75rem",
+                                        opacity: 0.6,
+                                        transition: "opacity 0.2s ease-in-out",
+                                        ml: 0.5,
+                                        flexShrink: 0,
+                                    }}
+                                />
+                            </Link>
+                            <Link
+                                href={getDetailsUrl(modelName)}
+                                target="_blank"
+                                rel="noopener noreferrer"
+                                aria-label={`View detailed evaluation results for ${modelName}`}
+                                title={TABLE_TOOLTIPS.EVAL_RESULTS(modelName)}
+                                sx={{
+                                    textDecoration: "none",
+                                    "&:hover": {
+                                        textDecoration: "underline",
+                                        "& svg": {
+                                            color: "text.primary",
+                                        },
+                                    },
+                                    display: "flex",
+                                    alignItems: "center",
+                                    color: "text.secondary",
+                                    flexShrink: 0,
+                                    mr: 0,
+                                }}
+                            >
+                                <DatabaseIcon />
+                            </Link>
+                        </Box>
+                    </Box>
+                );
+            },
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["id"],
         },
-        cellStyle: (value) => ({
-          position: "relative",
-          overflow: "hidden",
-          padding: "8px 16px",
-          borderLeft: (theme) =>
-            `2px solid ${alpha(
-              theme.palette.divider,
-              theme.palette.mode === "dark" ? 0.1 : 0.2
-            )}`,
-          borderRight: (theme) =>
-            `2px solid ${alpha(
-              theme.palette.divider,
-              theme.palette.mode === "dark" ? 0.1 : 0.2
-            )}`,
-        }),
-      },
-    },
-  ];
-  const createScoreCell = (getValue, row, field) => {
-    const value = getValue();
-    const rawValue = field.includes("normalized")
-      ? row.original.evaluations[field.split(".")[1]]?.value
-      : value;
+        {
+            accessorKey: "model.average_score",
+            header: createHeaderCell("Average", COLUMN_TOOLTIPS.AVERAGE),
+            cell: ({ row, getValue }) =>
+                createScoreCell(getValue, row, "model.average_score"),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.average_score"],
+            meta: {
+                headerStyle: {
+                    borderLeft: (theme) =>
+                        `2px solid ${alpha(
+                            theme.palette.divider,
+                            theme.palette.mode === "dark" ? 0.1 : 0.2
+                        )}`,
+                    borderRight: (theme) =>
+                        `2px solid ${alpha(
+                            theme.palette.divider,
+                            theme.palette.mode === "dark" ? 0.1 : 0.2
+                        )}`,
+                },
+                cellStyle: (value) => ({
+                    position: "relative",
+                    overflow: "hidden",
+                    padding: "8px 16px",
+                    borderLeft: (theme) =>
+                        `2px solid ${alpha(
+                            theme.palette.divider,
+                            theme.palette.mode === "dark" ? 0.1 : 0.2
+                        )}`,
+                    borderRight: (theme) =>
+                        `2px solid ${alpha(
+                            theme.palette.divider,
+                            theme.palette.mode === "dark" ? 0.1 : 0.2
+                        )}`,
+                }),
+            },
+        },
+    ];
+    const createScoreCell = (getValue, row, field) => {
+        const value = getValue();
+        const rawValue = field.includes("normalized")
+            ? row.original.evaluations[field.split(".")[1]]?.value
+            : value;
 
-    const isAverageColumn = field === "model.average_score";
-    const hasNoValue = value === null || value === undefined;
+        const isAverageColumn = field === "model.average_score";
+        const hasNoValue = value === null || value === undefined;
 
-    return (
-      <Box sx={commonStyles.cellContainer}>
-        {!hasNoValue && (scoreDisplay === "normalized" || isAverageColumn) && (
-          <Box
-            sx={{
-              position: "absolute",
-              left: -16,
-              top: -16,
-              height: "calc(100% + 32px)",
-              width: `calc(${value}% + 16px)`,
-              backgroundColor: getColorForValue(value),
-              opacity: (theme) => (theme.palette.mode === "light" ? 0.1 : 0.2),
-              transition: "width 0.3s ease",
-              zIndex: 0,
-            }}
-          />
-        )}
-        <Box
-          sx={{
-            position: "relative",
-            display: "flex",
-            alignItems: "center",
-            gap: 1,
-            zIndex: 1,
-            pl: isAverageColumn && !hasNoValue ? 1 : 0,
-          }}
-        >
-          {isAverageColumn && !hasNoValue && (
-            <Box
-              sx={{
-                width: 10,
-                height: 10,
-                borderRadius: "50%",
-                marginLeft: -1,
-                backgroundColor: getColorForValue(value),
-              }}
-            />
-          )}
-          <Typography variant="body2">
-            {hasNoValue ? (
-              "-"
-            ) : (
-              <>
-                {isAverageColumn ? (
-                  <>
-                    {value.toFixed(2)}
-                    <span style={{ opacity: 0.5 }}> %</span>
-                  </>
-                ) : scoreDisplay === "normalized" ? (
-                  <>
-                    {value.toFixed(2)}
-                    <span style={{ opacity: 0.5 }}> %</span>
-                  </>
-                ) : (
-                  <>{rawValue.toFixed(2)}</>
-                )}
-              </>
-            )}
-          </Typography>
-        </Box>
-      </Box>
-    );
-  };
+        return (
+            <Box sx={commonStyles.cellContainer}>
+                {!hasNoValue &&
+                    (scoreDisplay === "normalized" || isAverageColumn) && (
+                        <Box
+                            sx={{
+                                position: "absolute",
+                                left: -16,
+                                top: -16,
+                                height: "calc(100% + 32px)",
+                                width: `calc(${value}% + 16px)`,
+                                backgroundColor: getColorForValue(value),
+                                opacity: (theme) =>
+                                    theme.palette.mode === "light" ? 0.1 : 0.2,
+                                transition: "width 0.3s ease",
+                                zIndex: 0,
+                            }}
+                        />
+                    )}
+                <Box
+                    sx={{
+                        position: "relative",
+                        display: "flex",
+                        alignItems: "center",
+                        gap: 1,
+                        zIndex: 1,
+                        pl: isAverageColumn && !hasNoValue ? 1 : 0,
+                    }}
+                >
+                    {isAverageColumn && !hasNoValue && (
+                        <Box
+                            sx={{
+                                width: 10,
+                                height: 10,
+                                borderRadius: "50%",
+                                marginLeft: -1,
+                                backgroundColor: getColorForValue(value),
+                            }}
+                        />
+                    )}
+                    <Typography variant="body2">
+                        {hasNoValue ? (
+                            "-"
+                        ) : (
+                            <>
+                                {isAverageColumn ? (
+                                    <>
+                                        {value.toFixed(2)}
+                                        <span style={{ opacity: 0.5 }}> %</span>
+                                    </>
+                                ) : scoreDisplay === "normalized" ? (
+                                    <>
+                                        {value.toFixed(2)}
+                                        <span style={{ opacity: 0.5 }}> %</span>
+                                    </>
+                                ) : (
+                                    <>{rawValue.toFixed(2)}</>
+                                )}
+                            </>
+                        )}
+                    </Typography>
+                </Box>
+            </Box>
+        );
+    };
 
-  const evaluationColumns = [
-    {
-      accessorKey: "evaluations.multifin.normalized_score",
-      header: createHeaderCell("MultiFin", COLUMN_TOOLTIPS.MULTIFIN),
-      cell: ({ row, getValue }) =>
-        createScoreCell(getValue, row, "evaluations.multifin.normalized_score"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
-        "evaluations.multifin.normalized_score"
-      ],
-    },
-    {
-      accessorKey: "evaluations.qa.normalized_score",
-      header: createHeaderCell("QA", COLUMN_TOOLTIPS.QA),
-      cell: ({ row, getValue }) =>
-        createScoreCell(getValue, row, "evaluations.qa.normalized_score"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
-        "evaluations.qa.normalized_score"
-      ],
-    },
-    {
-      accessorKey: "evaluations.fns.normalized_score",
-      header: createHeaderCell("FNS", COLUMN_TOOLTIPS.FNS),
-      cell: ({ row, getValue }) =>
-        createScoreCell(getValue, row, "evaluations.fns.normalized_score"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
-        "evaluations.fns.normalized_score"
-      ],
-    },
-    {
-      accessorKey: "evaluations.finnum.normalized_score",
-      header: createHeaderCell("FinNum", COLUMN_TOOLTIPS.FinNum),
-      cell: ({ row, getValue }) =>
-        createScoreCell(getValue, row, "evaluations.finnum.normalized_score"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
-        "evaluations.finnum.normalized_score"
-      ],
-    },
-    {
-      accessorKey: "evaluations.fintext.normalized_score",
-      header: createHeaderCell("FinText", COLUMN_TOOLTIPS.FinText),
-      cell: ({ row, getValue }) =>
-        createScoreCell(getValue, row, "evaluations.fintext.normalized_score"),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
-        "evaluations.fintext.normalized_score"
-      ],
-    },
-  ];
+    const evaluationColumns = [
+        {
+            accessorKey: "evaluations.bc5cdr_chemical.normalized_score",
+            header: createHeaderCell(
+                "BC5CDR-chemical",
+                COLUMN_TOOLTIPS.BC5CDR_CHEMICAL
+            ),
+            cell: ({ row, getValue }) =>
+                createScoreCell(
+                    getValue,
+                    row,
+                    "evaluations.bc5cdr_chemical.normalized_score"
+                ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "evaluations.bc5cdr_chemical.normalized_score"
+            ],
+        },
+        {
+            accessorKey: "evaluations.ncbi_disease.normalized_score",
+            header: createHeaderCell(
+                "NCBI Disease",
+                COLUMN_TOOLTIPS.NCBI_DISEASE
+            ),
+            cell: ({ row, getValue }) =>
+                createScoreCell(
+                    getValue,
+                    row,
+                    "evaluations.ncbi_disease.normalized_score"
+                ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "evaluations.ncbi_disease.normalized_score"
+            ],
+        },
+        {
+            accessorKey: "evaluations.chemprot.normalized_score",
+            header: createHeaderCell("ChemProt", COLUMN_TOOLTIPS.CHEMPROT),
+            cell: ({ row, getValue }) =>
+                createScoreCell(
+                    getValue,
+                    row,
+                    "evaluations.chemprot.normalized_score"
+                ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "evaluations.chemprot.normalized_score"
+            ],
+        },
+        {
+            accessorKey: "evaluations.ddi2013.normalized_score",
+            header: createHeaderCell("DDI2013", COLUMN_TOOLTIPS.DDI2013),
+            cell: ({ row, getValue }) =>
+                createScoreCell(
+                    getValue,
+                    row,
+                    "evaluations.ddi2013.normalized_score"
+                ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "evaluations.ddi2013.normalized_score"
+            ],
+        },
+        {
+            accessorKey: "evaluations.hoc.normalized_score",
+            header: createHeaderCell("HoC", COLUMN_TOOLTIPS.HOC),
+            cell: ({ row, getValue }) =>
+                createScoreCell(
+                    getValue,
+                    row,
+                    "evaluations.hoc.normalized_score"
+                ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "evaluations.hoc.normalized_score"
+            ],
+        },
+        {
+            accessorKey: "evaluations.litcovid.normalized_score",
+            header: createHeaderCell("LitCovid", COLUMN_TOOLTIPS.LITCOVID),
+            cell: ({ row, getValue }) =>
+                createScoreCell(
+                    getValue,
+                    row,
+                    "evaluations.litcovid.normalized_score"
+                ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "evaluations.litcovid.normalized_score"
+            ],
+        },
+        {
+            accessorKey: "evaluations.medqa.normalized_score",
+            header: createHeaderCell("MedQA (5-Option)", COLUMN_TOOLTIPS.MEDQA),
+            cell: ({ row, getValue }) =>
+                createScoreCell(
+                    getValue,
+                    row,
+                    "evaluations.medqa.normalized_score"
+                ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "evaluations.medqa.normalized_score"
+            ],
+        },
+        {
+            accessorKey: "evaluations.pubmedqa.normalized_score",
+            header: createHeaderCell("PubMedQA", COLUMN_TOOLTIPS.PUBMEDQA),
+            cell: ({ row, getValue }) =>
+                createScoreCell(
+                    getValue,
+                    row,
+                    "evaluations.pubmedqa.normalized_score"
+                ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "evaluations.pubmedqa.normalized_score"
+            ],
+        },
+        {
+            accessorKey: "evaluations.pubmed.normalized_score",
+            header: createHeaderCell("PubMed", COLUMN_TOOLTIPS.PUBMED),
+            cell: ({ row, getValue }) =>
+                createScoreCell(
+                    getValue,
+                    row,
+                    "evaluations.pubmed.normalized_score"
+                ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "evaluations.pubmed.normalized_score"
+            ],
+        },
+        {
+            accessorKey: "evaluations.ms2.normalized_score",
+            header: createHeaderCell("MS^2", COLUMN_TOOLTIPS.MS2),
+            cell: ({ row, getValue }) =>
+                createScoreCell(
+                    getValue,
+                    row,
+                    "evaluations.ms2.normalized_score"
+                ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "evaluations.ms2.normalized_score"
+            ],
+        },
+        {
+            accessorKey: "evaluations.cochrane_pls.normalized_score",
+            header: createHeaderCell(
+                "Cochrane PLS",
+                COLUMN_TOOLTIPS.COCHRANE_PLS
+            ),
+            cell: ({ row, getValue }) =>
+                createScoreCell(
+                    getValue,
+                    row,
+                    "evaluations.cochrane_pls.normalized_score"
+                ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "evaluations.cochrane_pls.normalized_score"
+            ],
+        },
+        {
+            accessorKey: "evaluations.plos.normalized_score",
+            header: createHeaderCell("PLOS", COLUMN_TOOLTIPS.PLOS),
+            cell: ({ row, getValue }) =>
+                createScoreCell(
+                    getValue,
+                    row,
+                    "evaluations.plos.normalized_score"
+                ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "evaluations.plos.normalized_score"
+            ],
+        },
+    ];
 
-  const optionalColumns = [
-    {
-      accessorKey: "model.architecture",
-      header: createHeaderCell("Architecture", COLUMN_TOOLTIPS.ARCHITECTURE),
-      accessorFn: (row) => row.model.architecture,
-      cell: ({ row }) => (
-        <Tooltip title={row.original.model.architecture || "-"}>
-          <span>{row.original.model.architecture || "-"}</span>
-        </Tooltip>
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.architecture"],
-    },
-    {
-      accessorKey: "model.precision",
-      header: createHeaderCell("Precision", COLUMN_TOOLTIPS.PRECISION),
-      accessorFn: (row) => row.model.precision,
-      cell: ({ row }) => (
-        <Tooltip title={row.original.model.precision || "-"}>
-          <span>{row.original.model.precision || "-"}</span>
-        </Tooltip>
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.precision"],
-    },
-    {
-      accessorKey: "metadata.params_billions",
-      header: createHeaderCell("Parameters", COLUMN_TOOLTIPS.PARAMETERS),
-      cell: ({ row }) => (
-        <Box
-          sx={{
-            display: "flex",
-            alignItems: "center",
-            justifyContent: "flex-start",
-          }}
-        >
-          <Typography variant="body2">
-            {row.original.metadata.params_billions}
-            <span style={{ opacity: 0.6 }}>B</span>
-          </Typography>
-        </Box>
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.params_billions"],
-    },
-    {
-      accessorKey: "metadata.hub_license",
-      header: createHeaderCell("License", COLUMN_TOOLTIPS.LICENSE),
-      cell: ({ row }) => (
-        <Tooltip title={row.original.metadata.hub_license || "-"}>
-          <Typography
-            variant="body2"
-            sx={{
-              overflow: "hidden",
-              textOverflow: "ellipsis",
-              whiteSpace: "nowrap",
-            }}
-          >
-            {row.original.metadata.hub_license || "-"}
-          </Typography>
-        </Tooltip>
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.hub_license"],
-    },
-    {
-      accessorKey: "metadata.hub_hearts",
-      header: createHeaderCell(
-        "Hub ❤️",
-        "Number of likes received on the Hugging Face Hub"
-      ),
-      cell: ({ row }) => (
-        <Typography variant="body2">
-          {row.original.metadata.hub_hearts}
-        </Typography>
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.hub_hearts"],
-    },
-    {
-      accessorKey: "metadata.upload_date",
-      header: createHeaderCell(
-        "Upload Date",
-        "Date when the model was uploaded to the Hugging Face Hub"
-      ),
-      cell: ({ row }) => (
-        <Tooltip title={row.original.metadata.upload_date || "-"}>
-          <Typography
-            variant="body2"
-            sx={{
-              overflow: "hidden",
-              textOverflow: "ellipsis",
-              whiteSpace: "nowrap",
-            }}
-          >
-            {row.original.metadata.upload_date || "-"}
-          </Typography>
-        </Tooltip>
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.upload_date"],
-    },
-    {
-      accessorKey: "metadata.submission_date",
-      header: createHeaderCell(
-        "Submission Date",
-        "Date when the model was submitted to the leaderboard"
-      ),
-      cell: ({ row }) => (
-        <Tooltip title={row.original.metadata.submission_date || "-"}>
-          <Typography
-            variant="body2"
-            sx={{
-              overflow: "hidden",
-              textOverflow: "ellipsis",
-              whiteSpace: "nowrap",
-            }}
-          >
-            {row.original.metadata.submission_date || "-"}
-          </Typography>
-        </Tooltip>
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.submission_date"],
-    },
-    {
-      accessorKey: "metadata.generation",
-      header: createHeaderCell(
-        "Generation",
-        "The generation or version number of the model"
-      ),
-      cell: ({ row }) => (
-        <Typography variant="body2">
-          {row.original.metadata.generation}
-        </Typography>
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.generation"],
-    },
-    {
-      accessorKey: "metadata.base_model",
-      header: createHeaderCell(
-        "Base Model",
-        "The original model this model was derived from"
-      ),
-      cell: ({ row }) => (
-        <Tooltip title={row.original.metadata.base_model || "-"}>
-          <Typography
-            variant="body2"
-            sx={{
-              overflow: "hidden",
-              textOverflow: "ellipsis",
-              whiteSpace: "nowrap",
-            }}
-          >
-            {row.original.metadata.base_model || "-"}
-          </Typography>
-        </Tooltip>
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.base_model"],
-    },
-    {
-      accessorKey: "metadata.co2_cost",
-      header: createHeaderCell("CO₂ Cost", COLUMN_TOOLTIPS.CO2_COST),
-      cell: ({ row }) => (
-        <Box
-          sx={{
-            display: "flex",
-            alignItems: "center",
-            justifyContent: "flex-start",
-          }}
-        >
-          <Typography variant="body2">
-            {row.original.metadata.co2_cost?.toFixed(2) || "0"}
-            <span style={{ opacity: 0.6 }}> kg</span>
-          </Typography>
-        </Box>
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.co2_cost"],
-    },
-    {
-      accessorKey: "model.has_chat_template",
-      header: createHeaderCell(
-        "Chat Template",
-        "Whether this model has a chat template defined"
-      ),
-      cell: ({ row }) => (
-        <BooleanValue value={row.original.model.has_chat_template} />
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.has_chat_template"],
-    },
-    {
-      accessorKey: "features.is_not_available_on_hub",
-      header: createHeaderCell(
-        "Hub Availability",
-        "Whether the model is available on the Hugging Face Hub"
-      ),
-      cell: ({ row }) => (
-        <BooleanValue value={row.original.features.is_not_available_on_hub} />
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
-        "features.is_not_available_on_hub"
-      ],
-    },
-    {
-      accessorKey: "features.is_highlighted_by_maintainer",
-      header: createHeaderCell(
-        "Official Providers",
-        "Models that are officially provided and maintained by their original creators or organizations"
-      ),
-      cell: ({ row }) => (
-        <BooleanValue
-          value={row.original.features.is_highlighted_by_maintainer}
-        />
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
-        "features.is_highlighted_by_maintainer"
-      ],
-      enableSorting: true,
-    },
-    {
-      accessorKey: "features.is_moe",
-      header: createHeaderCell(
-        "Mixture of Experts",
-        "Whether this model uses a Mixture of Experts architecture"
-      ),
-      cell: ({ row }) => <BooleanValue value={row.original.features.is_moe} />,
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["features.is_moe"],
-    },
-    {
-      accessorKey: "features.is_flagged",
-      header: createHeaderCell(
-        "Flag Status",
-        "Whether this model has been flagged for any issues"
-      ),
-      cell: ({ row }) => (
-        <BooleanValue value={row.original.features.is_flagged} />
-      ),
-      size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["features.is_flagged"],
-    },
-  ];
+    const optionalColumns = [
+        {
+            accessorKey: "model.architecture",
+            header: createHeaderCell(
+                "Architecture",
+                COLUMN_TOOLTIPS.ARCHITECTURE
+            ),
+            accessorFn: (row) => row.model.architecture,
+            cell: ({ row }) => (
+                <Tooltip title={row.original.model.architecture || "-"}>
+                    <span>{row.original.model.architecture || "-"}</span>
+                </Tooltip>
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.architecture"],
+        },
+        {
+            accessorKey: "model.precision",
+            header: createHeaderCell("Precision", COLUMN_TOOLTIPS.PRECISION),
+            accessorFn: (row) => row.model.precision,
+            cell: ({ row }) => (
+                <Tooltip title={row.original.model.precision || "-"}>
+                    <span>{row.original.model.precision || "-"}</span>
+                </Tooltip>
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["model.precision"],
+        },
+        {
+            accessorKey: "metadata.params_billions",
+            header: createHeaderCell("Parameters", COLUMN_TOOLTIPS.PARAMETERS),
+            cell: ({ row }) => (
+                <Box
+                    sx={{
+                        display: "flex",
+                        alignItems: "center",
+                        justifyContent: "flex-start",
+                    }}
+                >
+                    <Typography variant="body2">
+                        {row.original.metadata.params_billions}
+                        <span style={{ opacity: 0.6 }}>B</span>
+                    </Typography>
+                </Box>
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "metadata.params_billions"
+            ],
+        },
+        {
+            accessorKey: "metadata.hub_license",
+            header: createHeaderCell("License", COLUMN_TOOLTIPS.LICENSE),
+            cell: ({ row }) => (
+                <Tooltip title={row.original.metadata.hub_license || "-"}>
+                    <Typography
+                        variant="body2"
+                        sx={{
+                            overflow: "hidden",
+                            textOverflow: "ellipsis",
+                            whiteSpace: "nowrap",
+                        }}
+                    >
+                        {row.original.metadata.hub_license || "-"}
+                    </Typography>
+                </Tooltip>
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.hub_license"],
+        },
+        {
+            accessorKey: "metadata.hub_hearts",
+            header: createHeaderCell(
+                "Hub ❤️",
+                "Number of likes received on the Hugging Face Hub"
+            ),
+            cell: ({ row }) => (
+                <Typography variant="body2">
+                    {row.original.metadata.hub_hearts}
+                </Typography>
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.hub_hearts"],
+        },
+        {
+            accessorKey: "metadata.upload_date",
+            header: createHeaderCell(
+                "Upload Date",
+                "Date when the model was uploaded to the Hugging Face Hub"
+            ),
+            cell: ({ row }) => (
+                <Tooltip title={row.original.metadata.upload_date || "-"}>
+                    <Typography
+                        variant="body2"
+                        sx={{
+                            overflow: "hidden",
+                            textOverflow: "ellipsis",
+                            whiteSpace: "nowrap",
+                        }}
+                    >
+                        {row.original.metadata.upload_date || "-"}
+                    </Typography>
+                </Tooltip>
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.upload_date"],
+        },
+        {
+            accessorKey: "metadata.submission_date",
+            header: createHeaderCell(
+                "Submission Date",
+                "Date when the model was submitted to the leaderboard"
+            ),
+            cell: ({ row }) => (
+                <Tooltip title={row.original.metadata.submission_date || "-"}>
+                    <Typography
+                        variant="body2"
+                        sx={{
+                            overflow: "hidden",
+                            textOverflow: "ellipsis",
+                            whiteSpace: "nowrap",
+                        }}
+                    >
+                        {row.original.metadata.submission_date || "-"}
+                    </Typography>
+                </Tooltip>
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "metadata.submission_date"
+            ],
+        },
+        {
+            accessorKey: "metadata.generation",
+            header: createHeaderCell(
+                "Generation",
+                "The generation or version number of the model"
+            ),
+            cell: ({ row }) => (
+                <Typography variant="body2">
+                    {row.original.metadata.generation}
+                </Typography>
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.generation"],
+        },
+        {
+            accessorKey: "metadata.base_model",
+            header: createHeaderCell(
+                "Base Model",
+                "The original model this model was derived from"
+            ),
+            cell: ({ row }) => (
+                <Tooltip title={row.original.metadata.base_model || "-"}>
+                    <Typography
+                        variant="body2"
+                        sx={{
+                            overflow: "hidden",
+                            textOverflow: "ellipsis",
+                            whiteSpace: "nowrap",
+                        }}
+                    >
+                        {row.original.metadata.base_model || "-"}
+                    </Typography>
+                </Tooltip>
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.base_model"],
+        },
+        {
+            accessorKey: "metadata.co2_cost",
+            header: createHeaderCell("CO₂ Cost", COLUMN_TOOLTIPS.CO2_COST),
+            cell: ({ row }) => (
+                <Box
+                    sx={{
+                        display: "flex",
+                        alignItems: "center",
+                        justifyContent: "flex-start",
+                    }}
+                >
+                    <Typography variant="body2">
+                        {row.original.metadata.co2_cost?.toFixed(2) || "0"}
+                        <span style={{ opacity: 0.6 }}> kg</span>
+                    </Typography>
+                </Box>
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["metadata.co2_cost"],
+        },
+        {
+            accessorKey: "model.has_chat_template",
+            header: createHeaderCell(
+                "Chat Template",
+                "Whether this model has a chat template defined"
+            ),
+            cell: ({ row }) => (
+                <BooleanValue value={row.original.model.has_chat_template} />
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "model.has_chat_template"
+            ],
+        },
+        {
+            accessorKey: "features.is_not_available_on_hub",
+            header: createHeaderCell(
+                "Hub Availability",
+                "Whether the model is available on the Hugging Face Hub"
+            ),
+            cell: ({ row }) => (
+                <BooleanValue
+                    value={row.original.features.is_not_available_on_hub}
+                />
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "features.is_not_available_on_hub"
+            ],
+        },
+        {
+            accessorKey: "features.is_highlighted_by_maintainer",
+            header: createHeaderCell(
+                "Official Providers",
+                "Models that are officially provided and maintained by their original creators or organizations"
+            ),
+            cell: ({ row }) => (
+                <BooleanValue
+                    value={row.original.features.is_highlighted_by_maintainer}
+                />
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES[
+                "features.is_highlighted_by_maintainer"
+            ],
+            enableSorting: true,
+        },
+        {
+            accessorKey: "features.is_moe",
+            header: createHeaderCell(
+                "Mixture of Experts",
+                "Whether this model uses a Mixture of Experts architecture"
+            ),
+            cell: ({ row }) => (
+                <BooleanValue value={row.original.features.is_moe} />
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["features.is_moe"],
+        },
+        {
+            accessorKey: "features.is_flagged",
+            header: createHeaderCell(
+                "Flag Status",
+                "Whether this model has been flagged for any issues"
+            ),
+            cell: ({ row }) => (
+                <BooleanValue value={row.original.features.is_flagged} />
+            ),
+            size: TABLE_DEFAULTS.COLUMNS.COLUMN_SIZES["features.is_flagged"],
+        },
+    ];
 
-  // Utiliser directement columnVisibility
-  const finalColumns = [
-    ...baseColumns,
-    ...evaluationColumns.filter((col) => columnVisibility[col.accessorKey]),
-    ...optionalColumns
-      .filter((col) => columnVisibility[col.accessorKey])
-      .sort((a, b) => {
-        // Définir l'ordre personnalisé des colonnes
-        const order = {
-          "model.architecture": 1,
-          "model.precision": 2,
-          "metadata.params_billions": 3,
-          "metadata.hub_license": 4,
-          "metadata.co2_cost": 5,
-          "metadata.hub_hearts": 6,
-          "metadata.upload_date": 7,
-          "metadata.submission_date": 8,
-          "metadata.generation": 9,
-          "metadata.base_model": 10,
-          "model.has_chat_template": 11,
-          "features.is_not_available_on_hub": 12,
-          "features.is_highlighted_by_maintainer": 13,
-          "features.is_moe": 14,
-          "features.is_flagged": 15,
-        };
-        return order[a.accessorKey] - order[b.accessorKey];
-      }),
-  ];
+    // Utiliser directement columnVisibility
+    const finalColumns = [
+        ...baseColumns,
+        ...evaluationColumns.filter((col) => columnVisibility[col.accessorKey]),
+        ...optionalColumns
+            .filter((col) => columnVisibility[col.accessorKey])
+            .sort((a, b) => {
+                // Définir l'ordre personnalisé des colonnes
+                const order = {
+                    "model.architecture": 1,
+                    "model.precision": 2,
+                    "metadata.params_billions": 3,
+                    "metadata.hub_license": 4,
+                    "metadata.co2_cost": 5,
+                    "metadata.hub_hearts": 6,
+                    "metadata.upload_date": 7,
+                    "metadata.submission_date": 8,
+                    "metadata.generation": 9,
+                    "metadata.base_model": 10,
+                    "model.has_chat_template": 11,
+                    "features.is_not_available_on_hub": 12,
+                    "features.is_highlighted_by_maintainer": 13,
+                    "features.is_moe": 14,
+                    "features.is_flagged": 15,
+                };
+                return order[a.accessorKey] - order[b.accessorKey];
+            }),
+    ];
 
-  return finalColumns;
+    return finalColumns;
 };