| # /// script | |
| # requires-python = ">=3.12" | |
| # dependencies = [ | |
| # "torch", | |
| # "torchvision", | |
| # "transformers", | |
| # "accelerate", | |
| # "peft", | |
| # ] | |
| # /// | |
| try: | |
| # Use a pipeline as a high-level helper | |
| from transformers import pipeline | |
| pipe = pipeline("image-text-to-text", model="Qwen/Qwen3-VL-2B-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?"} | |
| ] | |
| }, | |
| ] | |
| pipe(text=messages) | |
| with open('Qwen_Qwen3-VL-2B-Instruct_0.txt', 'w', encoding='utf-8') as f: | |
| f.write('Everything was good in Qwen_Qwen3-VL-2B-Instruct_0.txt') | |
| except Exception as e: | |
| with open('Qwen_Qwen3-VL-2B-Instruct_0.txt', 'w', encoding='utf-8') as f: | |
| import traceback | |
| traceback.print_exc(file=f) | |
| finally: | |
| from huggingface_hub import upload_file | |
| upload_file( | |
| path_or_fileobj='Qwen_Qwen3-VL-2B-Instruct_0.txt', | |
| repo_id='model-metadata/code_execution_files', | |
| path_in_repo='Qwen_Qwen3-VL-2B-Instruct_0.txt', | |
| repo_type='dataset', | |
| ) | |