correction

app.py

@@ -306,15 +306,16 @@ VOCAB_FILE = "vocabs_enhanced.pkl"
 CHECKPOINT_FILE = "checkpoint_enhanced.pt"
 
 # IMPORTANT: Update this with your actual Hugging Face repository ID
-REPO_ID = os.environ.get("SPACE_ID", "heerjtdev/LSTM_CRF")  # Replace with your repo ID
-HF_TOKEN = os.environ.get("HF_TOKEN")  # Set this as a secret in your Space settings
+REPO_ID = "heerjtdev/LSTM_CRF"  # Replace with your repo ID
+# HF_TOKEN = os.environ.get("HF_TOKEN")  # Set this as a secret in your Space settings
 
 
 def download_existing_models():
     """Download existing model files from the Hugging Face Hub if available."""
     try:
         api = HfApi()
-        files = api.list_repo_files(REPO_ID, token=HF_TOKEN)
+        #files = api.list_repo_files(REPO_ID, token=HF_TOKEN)
+        files = api.list_repo_files(REPO_ID)
 
         os.makedirs(OUTPUT_DIR, exist_ok=True)
 
@@ -326,7 +327,7 @@ def download_existing_models():
             model_path = hf_hub_download(
                 repo_id=REPO_ID,
                 filename=MODEL_FILE,
-                token=HF_TOKEN,
+                # token=HF_TOKEN,
                 local_dir=OUTPUT_DIR,
                 force_download=True  # Always get latest version
             )
@@ -339,7 +340,7 @@ def download_existing_models():
             vocab_path = hf_hub_download(
                 repo_id=REPO_ID,
                 filename=VOCAB_FILE,
-                token=HF_TOKEN,
+                # token=HF_TOKEN,
                 local_dir=OUTPUT_DIR,
                 force_download=True  # Always get latest version
             )
@@ -352,7 +353,7 @@ def download_existing_models():
             checkpoint_path = hf_hub_download(
                 repo_id=REPO_ID,
                 filename=CHECKPOINT_FILE,
-                token=HF_TOKEN,
+                # token=HF_TOKEN,
                 local_dir=OUTPUT_DIR,
                 force_download=True
             )
@@ -454,7 +455,7 @@ def train_model(dataset_file, progress=gr.Progress()):
                     path_or_fileobj=model_path,
                     path_in_repo=MODEL_FILE,
                     repo_id=REPO_ID,
-                    token=HF_TOKEN,
+                    # token=HF_TOKEN,
                     commit_message="Update trained model"
                 )
                 upload_status.append(MODEL_FILE)
@@ -468,7 +469,7 @@ def train_model(dataset_file, progress=gr.Progress()):
                     path_or_fileobj=vocab_path,
                     path_in_repo=VOCAB_FILE,
                     repo_id=REPO_ID,
-                    token=HF_TOKEN,
+                    # token=HF_TOKEN,
                     commit_message="Update vocabulary"
                 )
                 upload_status.append(VOCAB_FILE)
@@ -483,7 +484,7 @@ def train_model(dataset_file, progress=gr.Progress()):
                     path_or_fileobj=checkpoint_path,
                     path_in_repo=CHECKPOINT_FILE,
                     repo_id=REPO_ID,
-                    token=HF_TOKEN,
+                    # token=HF_TOKEN,
                     commit_message="Update checkpoint"
                 )
                 upload_status.append(CHECKPOINT_FILE)
@@ -539,7 +540,8 @@ def download_models_from_hub():
         os.makedirs(OUTPUT_DIR, exist_ok=True)
 
         api = HfApi()
-        files = api.list_repo_files(REPO_ID, token=HF_TOKEN)
+        #files = api.list_repo_files(REPO_ID, token=HF_TOKEN)
+        files = api.list_repo_files(REPO_ID)
 
         downloaded_files = []
 
@@ -549,7 +551,7 @@ def download_models_from_hub():
             model_path = hf_hub_download(
                 repo_id=REPO_ID,
                 filename=MODEL_FILE,
-                token=HF_TOKEN,
+                # token=HF_TOKEN,
                 local_dir=OUTPUT_DIR,
                 force_download=True
             )
@@ -563,7 +565,7 @@ def download_models_from_hub():
             vocab_path = hf_hub_download(
                 repo_id=REPO_ID,
                 filename=VOCAB_FILE,
-                token=HF_TOKEN,
+                # token=HF_TOKEN,
                 local_dir=OUTPUT_DIR,
                 force_download=True
             )