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Create app.py
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app.py
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import os
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import gradio as gr
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from huggingface_hub import login
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from transformers import pipeline
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# 讛转讞讘专讜转 诇-Hugging Face 注诐 诪驻转讞 诪讛讙讚专讜转 讛住讜讚讜转
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token = os.environ.get("HF_TOKEN")
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if token:
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login(token)
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else:
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print("讗讝讛专讛: 诇讗 谞诪爪讗 诪驻转讞 HF_TOKEN!")
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# 讟注讬谞转 讛诪讜讚诇
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model_name = "google/gemma-3n-E2B-it-litert-preview"
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print(f"讟讜注谉 诪讜讚诇 {model_name}...")
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try:
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generator = pipeline(
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"text-generation",
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model=model_name,
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device_map="auto",
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torch_dtype="auto",
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model_kwargs={"quantization_config": {"load_in_4bit": True}}
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)
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print("讛诪讜讚诇 谞讟注谉 讘讛爪诇讞讛!")
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except Exception as e:
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print(f"砖讙讬讗讛 讘讟注讬谞转 讛诪讜讚诇: {str(e)}")
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generator = None
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def ask_model(prompt):
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if generator is None:
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return "讛诪讜讚诇 诇讗 谞讟注谉 讻专讗讜讬. 讘讚讜拽 讗转 讛诇讜讙讬诐."
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try:
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outputs = generator(
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[{"role": "user", "content": prompt}],
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max_new_tokens=200,
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return_full_text=False
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)
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return outputs[0]["generated_text"]
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except Exception as e:
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return f"砖讙讬讗讛 讘拽讘诇转 转砖讜讘讛: {str(e)}"
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demo = gr.Interface(
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fn=ask_model,
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inputs=gr.Textbox(lines=3, placeholder="砖讗诇 砖讗诇讛..."),
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outputs=gr.Textbox(label="转砖讜讘讛"),
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title="Genie - 爪'讗讟讘讜讟 Gemma 3n",
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description="爪'讗讟讘讜讟 诪讘讜住住 注诇 诪讜讚诇 Gemma 3n 砖诇 Google"
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)
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demo.launch()
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