Upload app.py

app.py

@@ -15,13 +15,14 @@ model_path = "Mat17892/t5small_enfr_opus"
 
 # Load tokenizer
 tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=True, legacy=False)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_path, token = os.getenv('huggingface_token'))
 
-# Load the base model (e.g., LLaMA)
-base_model = AutoModelForSeq2SeqLM.from_pretrained(base_model, token = os.getenv('huggingface_token'))
+# # Load the base model (e.g., LLaMA)
+# base_model = AutoModelForSeq2SeqLM.from_pretrained(base_model, token = os.getenv('huggingface_token'))
 
-# Load LoRA adapter
-from peft import PeftModel
-model = PeftModel.from_pretrained(base_model, model_path, token = os.getenv('huggingface_token'))
+# # Load LoRA adapter
+# from peft import PeftModel
+# model = PeftModel.from_pretrained(base_model, model_path, token = os.getenv('huggingface_token'))
 
 def respond(
     message: str,