setting model manually

app.py

@@ -1,17 +1,28 @@
 import os
 from fastapi import FastAPI
 from pydantic import BaseModel
-from transformers import pipeline
+from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
 
-# ✅ Force Hugging Face to store model files in a writable directory
+# ✅ Define a writable cache directory
 os.environ["TRANSFORMERS_CACHE"] = "/app/cache"
 
-app = FastAPI()
+# ✅ Ensure the cache directory exists
+os.makedirs("/app/cache", exist_ok=True)
+
+# ✅ Hugging Face model
+MODEL_NAME = "facebook/m2m100_418M"
+
+# ✅ Download the model manually before usage
+print("Downloading model...")
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, cache_dir="/app/cache")
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME, cache_dir="/app/cache")
+translator = pipeline("translation", model=model, tokenizer=tokenizer)
 
-# Load translation model (French)
-translator = pipeline("translation", model="facebook/m2m100_418M")
+print("Model loaded successfully!")
+
+# ✅ FastAPI App
+app = FastAPI()
 
-# Request model
 class TextRequest(BaseModel):
     text: str
 

requirements.txt

@@ -1,5 +1,5 @@
+sentencepiece
 fastapi
 uvicorn
 transformers
 torch
-sentencepiece