Update app.py

app.py

@@ -1,21 +1,22 @@
-import gradio as gr
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 import os
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
 
 MODEL_NAME = "hpyapali/tinyllama-workout"
 
-# Retrieve API key from Hugging Face Secrets
-HF_TOKEN = os.getenv("HF_API_TOKEN")
+# Retrieve API key from environment variable
+HF_TOKEN = os.getenv("HF_TOKEN")
 
-# Load model with authentication
-tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_auth_token=HF_TOKEN)
-model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, use_auth_token=HF_TOKEN)
+# Authenticate model download
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, token=HF_TOKEN)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, token=HF_TOKEN)
 pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
 
 def workout_recommendation(prompt):
     result = pipe(prompt, max_length=50, do_sample=True)
     return result[0]["generated_text"]
 
+# Gradio Interface
+import gradio as gr
 iface = gr.Interface(
     fn=workout_recommendation,
     inputs="text",