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