Upload Qwen_Qwen3-VL-8B-Instruct_2.py with huggingface_hub

Qwen_Qwen3-VL-8B-Instruct_2.py

@@ -11,30 +11,8 @@
 # ///
 
 try:
-    # Load model directly
-    from transformers import AutoProcessor, AutoModelForVision2Seq
-    
-    processor = AutoProcessor.from_pretrained("Qwen/Qwen3-VL-8B-Instruct")
-    model = AutoModelForVision2Seq.from_pretrained("Qwen/Qwen3-VL-8B-Instruct")
-    messages = [
-        {
-            "role": "user",
-            "content": [
-                {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
-                {"type": "text", "text": "What animal is on the candy?"}
-            ]
-        },
-    ]
-    inputs = processor.apply_chat_template(
-    	messages,
-    	add_generation_prompt=True,
-    	tokenize=True,
-    	return_dict=True,
-    	return_tensors="pt",
-    ).to(model.device)
-    
-    outputs = model.generate(**inputs, max_new_tokens=40)
-    print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
+    import os
+    os.environ['HF_TOKEN'] = 'YOUR_TOKEN_HERE'
     with open('Qwen_Qwen3-VL-8B-Instruct_2.txt', 'w', encoding='utf-8') as f:
         f.write('Everything was good in Qwen_Qwen3-VL-8B-Instruct_2.txt')
 except Exception as e:
@@ -49,30 +27,8 @@ except Exception as e:
     with open('Qwen_Qwen3-VL-8B-Instruct_2.txt', 'a', encoding='utf-8') as f:
         import traceback
         f.write('''```CODE: 
-# Load model directly
-from transformers import AutoProcessor, AutoModelForVision2Seq
-
-processor = AutoProcessor.from_pretrained("Qwen/Qwen3-VL-8B-Instruct")
-model = AutoModelForVision2Seq.from_pretrained("Qwen/Qwen3-VL-8B-Instruct")
-messages = [
-    {
-        "role": "user",
-        "content": [
-            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
-            {"type": "text", "text": "What animal is on the candy?"}
-        ]
-    },
-]
-inputs = processor.apply_chat_template(
-	messages,
-	add_generation_prompt=True,
-	tokenize=True,
-	return_dict=True,
-	return_tensors="pt",
-).to(model.device)
-
-outputs = model.generate(**inputs, max_new_tokens=40)
-print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
+import os
+os.environ['HF_TOKEN'] = 'YOUR_TOKEN_HERE'
 ```
 
 ERROR: