| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForCausalLM, AutoProcessor | |
| from huggingface_hub import login | |
| import os | |
| import torch | |
| HF_TOKEN = os.environ.get("HF_TOKEN") | |
| login(token=HF_TOKEN) | |
| MODEL_ID = "Qwen/Qwen-VL-Chat-Int4" | |
| processor = AutoProcessor.from_pretrained(MODEL_ID, trust_remote_code=True, token=HF_TOKEN) | |
| model = AutoModelForCausalLM.from_pretrained(MODEL_ID, trust_remote_code=True, device_map="auto", token=HF_TOKEN) | |
| model.eval() | |
| def ask(image, prompt): | |
| inputs = processor(images=image, text=prompt, return_tensors="pt").to(model.device) | |
| outputs = model.generate(**inputs, max_new_tokens=512) | |
| response = processor.batch_decode(outputs, skip_special_tokens=True)[0] | |
| return response | |
| demo = gr.Interface( | |
| fn=ask, | |
| inputs=[gr.Image(type="pil"), gr.Textbox(label="請輸入問題")], | |
| outputs="text", | |
| title="🧠 Qwen1.5-VL 圖文問答 Demo" | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |