v

server.py

@@ -1,17 +0,0 @@
-import uvicorn
-from fastapi import FastAPI
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-app = FastAPI()
-
-model_name = 'facebook/incoder-1B'
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name, low_cpu_mem_usage=True)
-print('load ok')
-
-@app.get("/")
-def read_root(input_text, max_length, top_p, top_k, num_beams, temperature, repetition_penalty):
-    inpt = tokenizer.encode(input_text, return_tensors="pt")
-    out = model.generate(inpt, max_length=int(max_length), top_p=float(top_p), top_k=float(top_k), temperature=float(temperature), num_beams=int(num_beams), repetition_penalty=float(repetition_penalty))
-    res = tokenizer.decode(out[0])
-    return {"text": res}