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girishwangikar
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6ce9885
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Parent(s):
3e2d679
Update app.py
Browse files
app.py
CHANGED
@@ -1,8 +1,28 @@
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import gradio as gr
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import torch
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from transformers import Qwen2VLForConditionalGeneration, AutoProcessor
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@@ -23,12 +43,11 @@ def array_to_image_path(image_array):
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# Load model and processor
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model = Qwen2VLForConditionalGeneration.from_pretrained(
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"Qwen/Qwen2-VL-2B-Instruct",
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trust_remote_code=True,
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torch_dtype=torch.float32,
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device_map="cpu"
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).eval()
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processor = AutoProcessor.from_pretrained("Qwen/Qwen2-VL-2B-Instruct"
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DESCRIPTION = "[Qwen2-VL-2B Demo (CPU Version)](https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct)"
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@@ -95,5 +114,10 @@ with gr.Blocks(css=css) as demo:
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submit_btn.click(run_example, [input_img, text_input], [output_text])
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demo.queue(api_open=False)
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demo.launch(inline=False, server_name="0.0.0.0", server_port=int(os.getenv("PORT", 7860)), debug=True,
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The error you're encountering stems from two separate issues:
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1. **`trust_remote_code` warning:**
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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:
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```python
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model = Qwen2VLForConditionalGeneration.from_pretrained(
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"Qwen/Qwen2-VL-2B-Instruct",
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torch_dtype=torch.float32,
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device_map="cpu"
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).eval()
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```
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2. **`enable_queue` argument in `launch`:**
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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:
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```python
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demo.launch(inline=False, server_name="0.0.0.0", server_port=int(os.getenv("PORT", 7860)), debug=True, queue=False)
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```
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This should resolve the issues you're encountering. Here's the corrected code:
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### Final Code Fix:
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```python
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import gradio as gr
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import torch
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from transformers import Qwen2VLForConditionalGeneration, AutoProcessor
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# Load model and processor
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model = Qwen2VLForConditionalGeneration.from_pretrained(
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"Qwen/Qwen2-VL-2B-Instruct",
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torch_dtype=torch.float32,
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device_map="cpu"
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).eval()
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processor = AutoProcessor.from_pretrained("Qwen/Qwen2-VL-2B-Instruct")
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DESCRIPTION = "[Qwen2-VL-2B Demo (CPU Version)](https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct)"
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submit_btn.click(run_example, [input_img, text_input], [output_text])
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commandline_args = os.getenv("COMMANDLINE_ARGS", "")
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demo.queue(api_open=False)
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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))
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```
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This code should now work without the previous errors.
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