Update app.py

app.py

@@ -1,28 +1,3 @@
-The error you're encountering stems from two separate issues:
-
-1. **`trust_remote_code` warning:**
-   This warning is triggered because `trust_remote_code` is used in the wrong context. It only affects Auto classes (like `AutoModel` or `AutoProcessor`) but has no effect when loading the model directly using `Qwen2VLForConditionalGeneration`. You can safely remove it when loading the model. Here's the corrected model loading line:
-
-   ```python
-   model = Qwen2VLForConditionalGeneration.from_pretrained(
-       "Qwen/Qwen2-VL-2B-Instruct",
-       torch_dtype=torch.float32,
-       device_map="cpu"
-   ).eval()
-   ```
-
-2. **`enable_queue` argument in `launch`:**
-   The argument `enable_queue` has been replaced by `queue` in recent Gradio versions. Instead of using `enable_queue=False`, you should use `queue=False`. Here’s how to fix the `demo.launch()` call:
-
-   ```python
-   demo.launch(inline=False, server_name="0.0.0.0", server_port=int(os.getenv("PORT", 7860)), debug=True, queue=False)
-   ```
-
-This should resolve the issues you're encountering. Here's the corrected code:
-
-### Final Code Fix:
-
-```python
 import gradio as gr
 import torch
 from transformers import Qwen2VLForConditionalGeneration, AutoProcessor
@@ -117,7 +92,4 @@ with gr.Blocks(css=css) as demo:
 commandline_args = os.getenv("COMMANDLINE_ARGS", "")
 
 demo.queue(api_open=False)
-demo.launch(inline=False, server_name="0.0.0.0", server_port=int(os.getenv("PORT", 7860)), debug=True, queue=("--no-gradio-queue" not in commandline_args))
-```
-
-This code should now work without the previous errors.
+demo.launch(inline=False, server_name="0.0.0.0", server_port=int(os.getenv("PORT", 7860)), debug=True, queue=("--no-gradio-queue" not in commandline_args))