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import gradio as gr |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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MODEL_ID = "darkc0de/XortronCriminalComputingConfig" |
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tokenizer = AutoTokenizer.from_pretrained(MODEL_ID) |
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model = AutoModelForCausalLM.from_pretrained(MODEL_ID) |
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def respond(message, history): |
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inputs = tokenizer(message, return_tensors="pt") |
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outputs = model.generate( |
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**inputs, |
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max_new_tokens=256, |
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do_sample=True, |
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temperature=0.7, |
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top_p=0.9, |
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) |
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reply = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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return reply |
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demo = gr.ChatInterface( |
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fn=respond, |
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type="messages", |
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chatbot=gr.Chatbot(height=600, show_copy_button=True), |
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textbox=gr.Textbox(placeholder="Chat with Xortron...", container=False, scale=7), |
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title="Xortron Chat", |
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) |
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if __name__ == "__main__": |
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demo.launch() |
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