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import gradio as gr |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_name = "PygmalionAI/pygmalion-13b" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto") |
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def chat(prompt): |
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inputs = tokenizer(prompt, return_tensors="pt") |
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outputs = model.generate(**inputs, max_new_tokens=200) |
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return tokenizer.decode(outputs[0], skip_special_tokens=True) |
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demo = gr.Interface(fn=chat, inputs="text", outputs="text") |
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demo.launch() |
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