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Upload Qwen_Qwen2.5-VL-7B-Instruct_0.py with huggingface_hub

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  1. Qwen_Qwen2.5-VL-7B-Instruct_0.py +25 -0
Qwen_Qwen2.5-VL-7B-Instruct_0.py CHANGED
@@ -26,6 +26,31 @@ try:
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  },
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  ]
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  pipe(text=messages)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  with open('Qwen_Qwen2.5-VL-7B-Instruct_0.txt', 'w') as f:
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  f.write('Everything was good in Qwen_Qwen2.5-VL-7B-Instruct_0.txt')
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  except Exception as e:
 
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  },
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  ]
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  pipe(text=messages)
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+
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+ # Load model directly
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+ from transformers import AutoProcessor, AutoModelForVision2Seq
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+
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+ processor = AutoProcessor.from_pretrained("Qwen/Qwen2.5-VL-7B-Instruct")
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+ model = AutoModelForVision2Seq.from_pretrained("Qwen/Qwen2.5-VL-7B-Instruct")
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+ messages = [
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+ {
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+ "role": "user",
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+ "content": [
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+ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
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+ {"type": "text", "text": "What animal is on the candy?"}
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+ ]
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+ },
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+ ]
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+ inputs = processor.apply_chat_template(
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+ messages,
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+ add_generation_prompt=True,
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+ tokenize=True,
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+ return_dict=True,
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+ return_tensors="pt",
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+ ).to(model.device)
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+
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+ outputs = model.generate(**inputs, max_new_tokens=40)
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+ print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
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  with open('Qwen_Qwen2.5-VL-7B-Instruct_0.txt', 'w') as f:
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  f.write('Everything was good in Qwen_Qwen2.5-VL-7B-Instruct_0.txt')
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  except Exception as e: