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Create app.py
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app.py
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import gradio as gr
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from transformers import AutoModelForCausalLM, AutoProcessor
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from PIL import Image
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import torch
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model_id = "skt/A.X-4.0-VL-Light"
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model = AutoModelForCausalLM.from_pretrained(
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model_id, trust_remote_code=True, torch_dtype=torch.bfloat16
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).to("cuda")
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processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
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def ask_image_question(image, text):
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messages = [{"role": "user", "content": [{"type": "image"}, {"type": "text", "text": text}]}]
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inputs = processor(images=[image], conversations=[messages], return_tensors="pt").to("cuda")
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generation_kwargs = {
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"max_new_tokens": 256,
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"top_p": 0.8,
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"temperature": 0.5,
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"top_k": 20,
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"repetition_penalty": 1.05,
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"do_sample": True,
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}
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generated_ids = model.generate(**inputs, **generation_kwargs)
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output = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
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return output
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gr.Interface(fn=ask_image_question,
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inputs=[gr.Image(type="pil"), gr.Textbox(label="μ§λ¬Έ")],
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outputs="text").launch()
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