Create app.py

app.py

@@ -0,0 +1,24 @@
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from fastapi import FastAPI, Request
+from pydantic import BaseModel
+import uvicorn
+
+app = FastAPI()
+
+model_name = "meta-llama/Meta-Llama-3.1-405B"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+class Query(BaseModel):
+    inputs: str
+
+@app.post("/generate")
+async def generate(query: Query):
+    inputs = tokenizer(query.inputs, return_tensors="pt")
+    outputs = model.generate(inputs["input_ids"])
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return {"generated_text": response}
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8000)