setting model manually

app.py

@@ -3,19 +3,21 @@ from fastapi import FastAPI
 from pydantic import BaseModel
 from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
 
-# ✅ Define a writable cache directory
-os.environ["TRANSFORMERS_CACHE"] = "/app/cache"
+# ✅ Set cache directory inside Hugging Face's allowed `/tmp/` folder
+CACHE_DIR = "/tmp/huggingface_cache"
+os.environ["TRANSFORMERS_CACHE"] = CACHE_DIR
+os.environ["HF_HOME"] = CACHE_DIR
+os.environ["HF_HUB_DISABLE_SYMLINKS"] = "1"  # Fixes permission issue
 
-# ✅ Ensure the cache directory exists
-os.makedirs("/app/cache", exist_ok=True)
+# ✅ Ensure cache directory exists
+os.makedirs(CACHE_DIR, exist_ok=True)
 
-# ✅ Hugging Face model
+# ✅ Load the 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")
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, cache_dir=CACHE_DIR)
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME, cache_dir=CACHE_DIR)
 translator = pipeline("translation", model=model, tokenizer=tokenizer)
 
 print("Model loaded successfully!")

requirements.txt

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