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import gradio as gr |
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import torch |
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from transformers import GPT2Tokenizer |
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from evo_model import EvoDecoderModel |
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from generate import generate_text |
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tokenizer = GPT2Tokenizer.from_pretrained("gpt2") |
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vocab_size = tokenizer.vocab_size |
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model = EvoDecoderModel(vocab_size) |
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model.load_state_dict(torch.load("evo_decoder.pt", map_location="cpu")) |
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model.eval() |
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def chat_with_evo(prompt): |
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response = generate_text(model, tokenizer, prompt) |
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return response |
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gr.Interface(fn=chat_with_evo, |
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inputs="text", |
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outputs="text", |
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title="🧠 EvoDecoder Chatbot", |
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description="Ask Evo anything. Powered by your trained EvoDecoder.").launch() |
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