Init for HF space

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
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+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+title: Blt Entropy Patcher
+emoji: ⚡
+colorFrom: green
+colorTo: red
+sdk: gradio
+sdk_version: 5.27.0
+python_version: 3.11.11
+app_file: app.py
+pinned: false
+license: cc-by-nc-4.0
+---
+
 # Byte Latent Transformer
 
 This repository contains code for our paper: "Byte Latent Transformer: Patches Scale Better Than Tokens"

app.py

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+import os
+import gradio as gr
+import torch
+# Removed matplotlib and plot_entropies imports
+
+# Assuming bytelatent library and its dependencies are installed
+from bytelatent.data.file_util import get_fs
+# from bytelatent.distributed import DistributedArgs, setup_torch_distributed # Not needed
+from bytelatent.generate_patcher import patcher_nocache
+from bytelatent.tokenizers.blt_tokenizer import BltTokenizer
+# Removed: from bytelatent.plotting.entropy_figure_via_matplot_lib import plot_entropies
+from bytelatent.args import TrainArgs
+from download_blt_weights import main as ensure_present
+
+# --- Global Setup (Consider loading models outside if necessary) ---
+# Kept inside the function for simplicity as before.
+
+def process_text(prompt: str, model_name: str = "blt-1b"):
+    """
+    Processes the input prompt using the ByteLatent model and returns decoded characters.
+
+    Args:
+        prompt: The input text string from the Gradio interface.
+        model_name: The name of the model to use.
+
+    Returns:
+        A string containing the decoded characters after processing, or an error message.
+    """
+    try:
+        # --- Model and Tokenizer Loading ---
+        consolidated_path = os.path.join("hf-weights", model_name)
+        train_args_path = os.path.join(consolidated_path, "params.json")
+
+        if not os.path.exists(train_args_path):
+             raise FileNotFoundError(f"Training args not found at {train_args_path}. "
+                                     f"Ensure model '{model_name}' is downloaded/available.")
+
+        fs = get_fs(train_args_path)
+        train_args = TrainArgs.model_validate_json(fs.read_text(train_args_path))
+
+        tokenizer = train_args.data.tokenizer_args.build()
+        assert isinstance(tokenizer, BltTokenizer)
+
+        patcher_args = train_args.data.patcher_args.model_copy(deep=True)
+        patcher_args.realtime_patching = True
+        device = "cuda" if torch.cuda.is_available() else "cpu"
+        print(f"Using device: {device}")
+        patcher_args.patching_device = device
+        patcher_args.device = device
+
+        print("Loading entropy model and patcher...")
+        entropy_model_dir = os.path.join(consolidated_path, "entropy_model")
+        if not os.path.exists(entropy_model_dir):
+             raise FileNotFoundError(f"Entropy model directory not found at {entropy_model_dir}.")
+
+        patcher_args.entropy_model_checkpoint_dir = entropy_model_dir
+        patcher = patcher_args.build()
+        # --- End Loading ---
+
+        # --- Processing ---
+        prompts = [prompt]
+        print(f"Processing prompt: '{prompt}'")
+        results = patcher_nocache(
+            prompts, tokenizer=tokenizer, patcher=patcher
+        )
+
+        if not results:
+            print("Processing returned no results.")
+            return "Processing completed, but no results were generated." # Return info message
+
+        batch_patch_lengths, batch_scores, batch_tokens = results
+        # Decode the first (and only) result in the batch
+        decoded_chars_list = [tokenizer.decode(row_tokens.tolist()) for row_tokens in batch_tokens]
+        decoded_output = decoded_chars_list[0] if decoded_chars_list else "No characters decoded."
+
+        print("Processing and decoding complete.")
+        # --- End Processing ---
+
+
+        # Return the decoded text string
+        return decoded_output
+
+    except FileNotFoundError as e:
+        print(f"Error: {e}")
+        # raise gr.Error(str(e)) # Display specific error in Gradio UI
+        return f"Error: {str(e)}" # Return error as text output
+    except Exception as e:
+        print(f"An unexpected error occurred: {e}")
+        import traceback
+        traceback.print_exc()
+        # raise gr.Error(f"An error occurred during processing: {e}")
+        return f"An unexpected error occurred: {e}" # Return error as text output
+
+
+# --- Gradio Interface Definition ---
+iface = gr.Interface(
+    fn=process_text,
+    inputs=gr.Textbox(
+        label="Input Prompt",
+        placeholder="Enter your text here..."
+    ),
+    # Changed output to display the decoded text
+    outputs=gr.Text(label="Decoded Output"),
+    title="ByteLatent Text Processor",
+    description="Enter text to process it with the ByteLatent model ('blt-1b' by default). The decoded output will be shown.",
+    allow_flagging="never",
+)
+
+# --- Launch the Gradio App ---
+if __name__ == "__main__":
+    ensure_present(["blt-1b"])
+    iface.launch()

original_blt_requirements.txt

@@ -0,0 +1,24 @@
+numpy
+omegaconf
+msgspec
+rouge-score
+sacrebleu
+sentencepiece
+tiktoken
+fsspec
+blobfile
+wandb
+viztracer
+lm-eval
+scipy
+pynvml
+datatrove
+orjson
+luigi
+pydantic
+altair
+submitit
+typer
+rich
+fsspec[full]
+orjson

requirements.txt

@@ -1,24 +1,364 @@
-numpy
-omegaconf
-msgspec
-rouge-score
-sacrebleu
-sentencepiece
-tiktoken
-fsspec
-blobfile
-wandb
-viztracer
-lm-eval
-scipy
-pynvml
-datatrove
-orjson
-luigi
-pydantic
-altair
-submitit
-typer
-rich
-fsspec[full]
-orjson
+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: linux-64
+_libgcc_mutex=0.1=main
+_openmp_mutex=5.1=1_gnu
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