| from transformers import AutoTokenizer, AutoModelForVision2Seq |
| import gradio as gr |
| from PIL import Image |
|
|
| |
| MODEL_NAME = "Qwen/Qwen2-VL-7B" |
| tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME) |
| model = AutoModelForVision2Seq.from_pretrained(MODEL_NAME) |
|
|
| def generate_response(image_path, text_prompt): |
| image = Image.open(image_path) |
| inputs = tokenizer(text_prompt, return_tensors="pt").to(model.device) |
| vision_inputs = model.processor(images=image, return_tensors="pt").to(model.device) |
| outputs = model.generate(**vision_inputs, **inputs) |
| return tokenizer.decode(outputs[0], skip_special_tokens=True) |
|
|
| |
| iface = gr.Interface( |
| fn=generate_response, |
| inputs=[gr.Image(type="filepath"), gr.Textbox(label="Text Prompt")], |
| outputs="text", |
| title="Qwen2-VL-7B Image + Text Generator" |
| ) |
|
|
| if __name__ == "__main__": |
| iface.launch() |
|
|
