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import gradio as gr |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import torch |
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model_name = "mistralai/Mistral-7B-Instruct-v0.3" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16).to("cuda") |
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def search(query): |
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inputs = tokenizer(query, return_tensors="pt").to("cuda") |
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outputs = model.generate(inputs.input_ids, max_length=256) |
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result = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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return result |
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iface = gr.Interface(fn=search, inputs="text", outputs="text", title="AI Search Engine") |
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if __name__ == "__main__": |
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iface.launch() |
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