Updating decription

app.py

@@ -31,7 +31,7 @@ class Config:
 
     # Bytelatent Specific
     BLT_WEIGHTS_DIR: str = "hf-weights"
-    BLT_MAX_BYTES_FOR_DEMO: float = math.inf # Limit for this specific demo's entropy model
+    BLT_MAX_BYTES_FOR_DEMO: float = math.inf if torch.cuda.is_available() else 512.0
 
     # Gradio
     DEFAULT_PROMPT: str = "Daenerys Targaryen is in Game of Thrones, a fantasy epic by George R.R. Martin."
@@ -39,7 +39,7 @@ class Config:
     GRADIO_TITLE: str = "BLT's Entropy-based Patcher vs. Tokenizer Visualisation"
     GRADIO_DESC: str = (
         "Enter text to visualize its segmentation according to different methods:\n"
-        f"1.  **Byte Latent Transformer (BLT):** Entropy-based patching plot and patched text (_for this space ONLY_ - limited to ~{BLT_MAX_BYTES_FOR_DEMO} bytes using `blt_main_entropy_100m_512w`).\n"
+        f"1.  **Byte Latent Transformer (BLT):** Entropy-based patching plot and patched text (using `blt_main_entropy_100m_512w`).\n"
         f"2.  **Tiktoken (GPT-4):** Text segmented by `{TIKTOKEN_ENCODING_NAME}` tokens.\n"
         f"3.  **Llama 3:** Text segmented by the `{LLAMA3_MODEL_NAME}` tokenizer."
     )
@@ -418,7 +418,7 @@ with gr.Blocks(theme=Config.GRADIO_THEME) as iface:
                 placeholder="Enter text here...",
                 # Max length is for UI input; Bytelatent truncation happens in backend
                 lines=5,
-                info=f"Note: Bytelatent processing is limited to ~{Config.BLT_MAX_BYTES_FOR_DEMO} bytes for this demo."
+                info="" if torch.cuda.is_available() else f"Note: Bytelatent processing is limited to ~{Config.BLT_MAX_BYTES_FOR_DEMO} bytes for this demo."
             )
             submit_button = gr.Button("Generate Visualizations", variant="primary")
             status_output = gr.Textbox(label="Processing Status", interactive=False, lines=10) # More space for detailed status