Update app.py

app.py

@@ -62,12 +62,12 @@ def process_model(model_id, q_method, use_imatrix, imatrix_q_method, private_rep
     if oauth_token.token is None:
         raise ValueError("You must be logged in to use GGUF-my-repo")
     model_name = model_id.split('/')[-1]
+    model_file = None
 
     try:
         api = HfApi(token=oauth_token.token)
         api.snapshot_download(repo_id=model_id, local_dir=model_name, local_dir_use_symlinks=False)
 
-        # Find all files in the downloaded model directory
         all_files = []
         for root, _, files in os.walk(model_name):
             for file in files:
@@ -76,7 +76,6 @@ def process_model(model_id, q_method, use_imatrix, imatrix_q_method, private_rep
         if not all_files:
             raise FileNotFoundError("No files found in the downloaded model directory.")
 
-        # Attempt conversion for all files, regardless of type
         for file_path in all_files:
             try:
                 gguf_model_file = f"{os.path.splitext(file_path)[0]}.gguf"
@@ -84,11 +83,11 @@ def process_model(model_id, q_method, use_imatrix, imatrix_q_method, private_rep
                 result = subprocess.run(conversion_command, shell=True, capture_output=True)
                 if result.returncode == 0:
                     model_file = gguf_model_file
-                    break  # Stop if a conversion is successful
+                    break
             except Exception as e:
                 print(f"Conversion attempt failed for {file_path}: {e}")
 
-        if not model_file:
+        if model_file is None:
             raise Exception("Unable to find or convert a suitable model file to GGUF format.")
 
         imatrix_path = "llama.cpp/imatrix.dat"
@@ -108,7 +107,6 @@ def process_model(model_id, q_method, use_imatrix, imatrix_q_method, private_rep
         quantized_gguf_name = f"{model_name.lower()}-{imatrix_q_method.lower()}-imat.gguf" if use_imatrix else f"{model_name.lower()}-{q_method.lower()}.gguf"
         quantized_gguf_path = quantized_gguf_name
 
-        # Quantize the model
         os.chdir("llama.cpp")
         if use_imatrix:
             quantise_ggml = f"./llama-quantize --imatrix {imatrix_path} ../{model_file} ../{quantized_gguf_path} {imatrix_q_method}"
@@ -123,13 +121,6 @@ def process_model(model_id, q_method, use_imatrix, imatrix_q_method, private_rep
         new_repo_url = api.create_repo(repo_id=f"{username}/{model_name}-{imatrix_q_method if use_imatrix else q_method}-GGUF", exist_ok=True, private=private_repo)
         new_repo_id = new_repo_url.repo_id
 
-        try:
-            card = ModelCard.load(model_id, token=oauth_token.token)
-        except:
-            card = ModelCard("")
-        if card.data.tags is None:
-            card.data.tags = []
-
         if split_model:
             split_upload_model(quantized_gguf_path, new_repo_id, oauth_token, split_max_tensors, split_max_size)
         else:
@@ -141,8 +132,7 @@ def process_model(model_id, q_method, use_imatrix, imatrix_q_method, private_rep
                 )
             except Exception as e:
                 raise Exception(f"Error uploading quantized model: {e}")
-        
-        
+
         if use_imatrix and os.path.isfile(imatrix_path):
             try:
                 api.upload_file(
@@ -153,12 +143,6 @@ def process_model(model_id, q_method, use_imatrix, imatrix_q_method, private_rep
             except Exception as e:
                 raise Exception(f"Error uploading imatrix.dat: {e}")
 
-        api.upload_file(
-            path_or_fileobj=f"README.md",
-            path_in_repo=f"README.md",
-            repo_id=new_repo_id,
-        )
-
         return (
             f'Find your repo <a href=\'{new_repo_url}\' target="_blank" style="text-decoration:underline">here</a>',
             "llama.png",