fix: update branding from InfraBench to InferBench in app.py for consistency across the platform

app.py

@@ -18,10 +18,10 @@ df = df[["Model"] + [col for col in df.columns.tolist() if col not in ["URL", "P
 with gr.Blocks("ParityError/Interstellar") as demo:
     gr.Markdown(
         """
-        <h1 style="margin: 0;">InfraBench - A Leaderboard for Inference Providers</h1>
+        <h1 style="margin: 0;">InferBench - A Leaderboard for Inference Providers</h1>
         <br>
         <div style="margin-bottom: 20px;">
-            <p>Welcome to InfraBench, the ultimate leaderboard for evaluating inference providers. Our platform focuses on key metrics such as cost, quality, and compression to help you make informed decisions. Whether you're a developer, researcher, or business looking to optimize your inference processes, InfraBench provides the insights you need to choose the best provider for your needs.</p>
+            <p>Welcome to InferBench, the ultimate leaderboard for evaluating inference providers. Our platform focuses on key metrics such as cost, quality, and compression to help you make informed decisions. Whether you're a developer, researcher, or business looking to optimize your inference processes, InferBench provides the insights you need to choose the best provider for your needs.</p>
         </div>
     """
     )
@@ -59,8 +59,8 @@ with gr.Blocks("ParityError/Interstellar") as demo:
                 # 💜 About Pruna AI
                 We are Pruna AI, an open source AI optimisation engine and we simply make your models cheaper, faster, smaller, greener!
 
-                # 📊 About InfraBench
-                InfraBench is a leaderboard for inference providers, focusing on cost, quality, and compression.
+                # 📊 About InferBench
+                InferBench is a leaderboard for inference providers, focusing on cost, quality, and compression.
                 Over the past few years, we’ve observed outstanding progress in image generation models fueled by ever-larger architectures.
                 Due to their size, state-of-the-art models such as FLUX take more than 6 seconds to generate a single image on a high-end H100 GPU.
                 While compression techniques can reduce inference time, their impact on quality often remains unclear.
@@ -89,8 +89,8 @@ with gr.Blocks("ParityError/Interstellar") as demo:
             gr.Markdown(
                 """
                     ```bibtex
-                    @article{InfraBench,
-                        title={InfraBench: A Leaderboard for Inference Providers},
+                    @article{InferBench,
+                        title={InferBench: A Leaderboard for Inference Providers},
                         author={PrunaAI},
                         year={2025},
                         howpublished={\\url{https://huggingface.co/spaces/PrunaAI/InferBench}}