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from transformers import GPT2Tokenizer, GPT2LMHeadModel |
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import gradio as gr |
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model = GPT2LMHeadModel.from_pretrained("genaforvena/the_soft_scum_gospel_delerizome_machine_a_thousand_guattaris") |
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tokenizer = GPT2Tokenizer.from_pretrained("genaforvena/the_soft_scum_gospel_delerizome_machine_a_thousand_guattaris") |
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tokenizer.pad_token = tokenizer.eos_token |
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def generate_text(prompt): |
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"""Generates text using the fine-tuned model.""" |
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inputs = tokenizer(prompt, return_tensors="pt", padding=True) |
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outputs = model.generate( |
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inputs["input_ids"], |
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attention_mask=inputs["attention_mask"], |
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max_length=150, |
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num_return_sequences=1, |
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do_sample=True, |
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temperature=0.8, |
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top_k=50, |
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pad_token_id=tokenizer.eos_token_id |
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) |
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return tokenizer.decode(outputs[0], skip_special_tokens=True) |
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iface = gr.Interface(fn=generate_text, inputs="text", outputs="text") |
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iface.launch() |
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