Deploy FastAPI model app

app.py

@@ -0,0 +1,18 @@
+from fastapi import FastAPI, Request
+from pydantic import BaseModel
+from model_inference import generate_code
+
+app = FastAPI()
+
+class Prompt(BaseModel):
+    prompt: str
+    max_tokens: int = 128
+
+@app.get("/")
+def home():
+    return {"message": "🧠 Model is online!"}
+
+@app.post("/generate")
+def generate(prompt: Prompt):
+    output = generate_code(prompt.prompt, prompt.max_tokens)
+    return {"output": output}

model_inference.py

@@ -0,0 +1,26 @@
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+MODEL_NAME = "NousResearch/Hermes-2-Pro-Mistral"  # ✅ Uncensored & efficient
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_fast=True)
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME,
+    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
+    device_map="auto"
+)
+model.eval()
+
+def generate_code(prompt: str, max_tokens: int = 256):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    with torch.no_grad():
+        output = model.generate(
+            inputs.input_ids,
+            max_new_tokens=max_tokens,
+            do_sample=True,
+            temperature=0.7,
+            top_p=0.95,
+            repetition_penalty=1.1,
+            pad_token_id=tokenizer.eos_token_id
+        )
+    return tokenizer.decode(output[0], skip_special_tokens=True)

requirements.txt

@@ -0,0 +1,4 @@
+transformers>=4.38.0
+torch
+fastapi
+uvicorn

space.yaml

@@ -0,0 +1,8 @@
+---
+
+## ✅ 6. (Optional) `Space.yaml` (for Hugging Face Spaces)
+
+```yaml
+sdk: docker
+app_file: app.py
+python_version: "3.9"