Fix HF authentication with secure environment variable handling

- Use environment variables for HF token (HF_TOKEN or HUGGINGFACE_HUB_TOKEN)
- Add proper error handling for missing tokens
- Remove duplicate UI elements
- No hardcoded tokens for security compliance

app.py

@@ -4,6 +4,7 @@ import torch
 import torch.nn.functional as F
 import os
 import sys
+from huggingface_hub import login
 
 from config import ModelArgs, get_args
 from model import DeepSeekV3, initialize_tokenizer
@@ -27,13 +28,37 @@ def initialize_app():
     # Initialize model args
     model_args = ModelArgs()
     
-    # Initialize tokenizer (no HF token needed for basic operation)
+    # Get HF token from environment variables (set in HF Spaces secrets)
+    hf_token = os.getenv('HF_TOKEN') or os.getenv('HUGGINGFACE_HUB_TOKEN')
+    
+    if not hf_token:
+        print("Warning: No HF_TOKEN found in environment variables.")
+        print("Please set HF_TOKEN in your Hugging Face Spaces secrets.")
+        print("Go to Settings -> Repository secrets -> New secret")
+        print("Name: HF_TOKEN, Value: your_huggingface_token")
+        # For now, we'll try to continue without authentication
+        hf_token = None
+    
+    # Login to Hugging Face Hub for gated model access
+    if hf_token:
+        try:
+            login(token=hf_token, add_to_git_credential=False)
+            print("Successfully logged in to Hugging Face Hub")
+        except Exception as e:
+            print(f"Warning: Could not login to HF Hub: {e}")
+    
+    # Initialize tokenizer with HF token for gated model access
     if tk is None:
-        tk = Tokenizer(hf_token=None)
-        tk = tk.ready_tokenizer()
+        try:
+            tk = Tokenizer(hf_token=hf_token)
+            tk = tk.ready_tokenizer()
+            print("Tokenizer initialized successfully")
+        except Exception as e:
+            print(f"Error initializing tokenizer: {e}")
+            raise e
     
     # Initialize the global tokenizer in model.py
-    initialize_tokenizer(hf_token=None)
+    initialize_tokenizer(hf_token=hf_token)
 
 def load_model(model_path, device, model_args):
     """Load model from checkpoint"""
@@ -138,15 +163,6 @@ def create_interface():
                         label="Top-k"
                     )
                 
-                with gr.Row():
-                    top_k_slider = gr.Slider(
-                        minimum=1,
-                        maximum=100,
-                        value=50,
-                        step=1,
-                        label="Top-k"
-                    )
-                
                 generate_btn = gr.Button("🎯 Generate Text", variant="primary", size="lg")
                 
             with gr.Column(scale=3):