Create main.py

main.py

@@ -0,0 +1,22 @@
+from fastapi import FastAPI
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+app = FastAPI()
+
+# Load model and tokenizer
+model_name = "mistralai/Mistral-7B-v0.1"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+# model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")
+
+# if these 3 lines didn't work use the one above
+from transformers import BitsAndBytesConfig
+quant_config = BitsAndBytesConfig(load_in_8bit=True)
+model = AutoModelForCausalLM.from_pretrained(model_name, quantization_config=quant_config, device_map="auto")
+
+
+@app.post("/generate")
+async def generate_text(prompt: str):
+    inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+    outputs = model.generate(**inputs, max_length=200)
+    return {"response": tokenizer.decode(outputs[0], skip_special_tokens=True)}