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from fastapi import FastAPI, Request |
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from transformers import AutoTokenizer, AutoModelForCasualLM |
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app = FastAPI() |
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tokenizer = AutoTokenizer.from_pretrained("togethercomputer/GPT-NeoXT-Chat-Base-20B") |
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model = AutoModelForCausalLM.from_pretrained("togethercomputer/GPT-NeoXT-Chat-Base-20B", torch_dtype=torch.bfloat16) |
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@app.get("/gpt") |
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async def gpt(prompt: str, req: Request): |
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inputs = tokenizer("<human>: Hello!\n<bot>:", return_tensors='pt').to(model.device) |
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outputs = model.generate(**inputs, max_new_tokens=10, do_sample=True, temperature=0.8) |
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output_str = tokenizer.decode(outputs[0]) |
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print(output_str) |
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return {"response": output_str} |
