Update app.py

app.py

@@ -3,14 +3,17 @@ import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
 import torch
 
-# Load model and tokenizer
-model_name = "meta-llama/Meta-Llama-3.2-3B-Instruct"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(
-    model_name,
-    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
-    device_map="auto"
-)
+model_name = "your-private-or-protected-model-id"
+hf_token = os.environ.get("HF_TOKEN")
+
+tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=hf_token)
+model = AutoModelForCausalLM.from_pretrained(model_name, use_auth_token=hf_token)
+
+# model = AutoModelForCausalLM.from_pretrained(
+#     model_name,
+#     torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
+#     device_map="auto"
+# )
 
 def generate_prompt(original, translation):
     return f"### Task: Machine Translation Quality Estimation\n\nSource: {original}\nTranslation: {translation}\n\nScore (0-1):"