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import gradio as gr |
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from transformers import GPT2LMHeadModel, GPT2Tokenizer |
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model_name = "HooshvareLab/gpt2-fa" |
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model = GPT2LMHeadModel.from_pretrained(model_name) |
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tokenizer = GPT2Tokenizer.from_pretrained(model_name) |
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def chat(input_text): |
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inputs = tokenizer.encode(input_text, return_tensors="pt") |
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outputs = model.generate(inputs, max_length=150, do_sample=True, top_k=50) |
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response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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return response |
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demo = gr.Interface(fn=chat, inputs="text", outputs="text", title="چتبات فارسی") |
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