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Browse files- app.py +16 -0
- requirements.txt +2 -0
app.py
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import gradio as gr
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from model import *
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model = GPTLanguageModel().to(device)
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model.load_state_dict(torch.load("mini-gpt.pth"))
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answer = decode(model.generate(context, max_new_tokens=1000)[0].tolist())
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def display(number):
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return answer[:number+1]
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input_slider = gr.inputs.Slider(minimum=500, maximum=1000, default=500, label="Select the maxium number of tokens/words:")
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output_text = gr.outputs.Textbox()
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gr.Interface(fn=display, inputs=input_slider, outputs=output_text).launch()
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requirements.txt
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torch
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gradio
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