diff --git a/README.md b/README.md
index 822deba..f36a8b9 100644
--- a/README.md
+++ b/README.md
@@ -156,7 +156,7 @@ text-generation-webui
 
 In the "Model" tab of the UI, those models can be automatically downloaded from Hugging Face. You can also download them via the command-line with `python download-model.py organization/model`.
 
-* GGML models are a single file and should be placed directly into `models`. Example:
+* GGUF models are a single file and should be placed directly into `models`. Example:
 
 ```
 text-generation-webui
@@ -258,7 +258,7 @@ Optionally, you can use the following command-line flags:
 | `--quant_type QUANT_TYPE`                   | quant_type for 4-bit. Valid options: nf4, fp4. |
 | `--use_double_quant`                        | use_double_quant for 4-bit. |
 
-#### GGML (for llama.cpp and ctransformers)
+#### GGUF (for llama.cpp and ctransformers)
 
 | Flag        | Description |
 |-------------|-------------|
diff --git a/download-model.py b/download-model.py
index a65f82c..be8d59f 100644
--- a/download-model.py
+++ b/download-model.py
@@ -57,7 +57,7 @@ class ModelDownloader:
         classifications = []
         has_pytorch = False
         has_pt = False
-        # has_ggml = False
+        # has_gguf = False
         has_safetensors = False
         is_lora = False
         while True:
@@ -78,10 +78,10 @@ class ModelDownloader:
                 is_pytorch = re.match(r"(pytorch|adapter|gptq)_model.*\.bin", fname)
                 is_safetensors = re.match(r".*\.safetensors", fname)
                 is_pt = re.match(r".*\.pt", fname)
-                is_ggml = re.match(r".*ggml.*\.bin", fname)
+                is_gguf = re.match(r'.*\.gguf', fname)
                 is_tokenizer = re.match(r"(tokenizer|ice|spiece).*\.model", fname)
                 is_text = re.match(r".*\.(txt|json|py|md)", fname) or is_tokenizer
-                if any((is_pytorch, is_safetensors, is_pt, is_ggml, is_tokenizer, is_text)):
+                if any((is_pytorch, is_safetensors, is_pt, is_gguf, is_tokenizer, is_text)):
                     if 'lfs' in dict[i]:
                         sha256.append([fname, dict[i]['lfs']['oid']])
 
@@ -101,9 +101,9 @@ class ModelDownloader:
                         elif is_pt:
                             has_pt = True
                             classifications.append('pt')
-                        elif is_ggml:
-                            # has_ggml = True
-                            classifications.append('ggml')
+                        elif is_gguf:
+                            # has_gguf = True
+                            classifications.append('gguf')
 
             cursor = base64.b64encode(f'{{"file_name":"{dict[-1]["path"]}"}}'.encode()) + b':50'
             cursor = base64.b64encode(cursor)
diff --git a/modules/llamacpp_hf.py b/modules/llamacpp_hf.py
index 4d42394..0608cb0 100644
--- a/modules/llamacpp_hf.py
+++ b/modules/llamacpp_hf.py
@@ -165,7 +165,7 @@ class LlamacppHF(PreTrainedModel):
         if path.is_file():
             model_file = path
         else:
-            model_file = list(path.glob('*ggml*.bin'))[0]
+            model_file = list(path.glob('*.gguf*'))[0]
 
         logger.info(f"llama.cpp weights detected: {model_file}\n")
 
diff --git a/modules/models.py b/modules/models.py
index ea9cc52..5268a2f 100644
--- a/modules/models.py
+++ b/modules/models.py
@@ -241,7 +241,7 @@ def llamacpp_loader(model_name):
     if path.is_file():
         model_file = path
     else:
-        model_file = list(Path(f'{shared.args.model_dir}/{model_name}').glob('*ggml*.bin'))[0]
+        model_file = list(Path(f'{shared.args.model_dir}/{model_name}').glob('*.gguf*'))[0]
 
     logger.info(f"llama.cpp weights detected: {model_file}")
     model, tokenizer = LlamaCppModel.from_pretrained(model_file)
diff --git a/modules/models_settings.py b/modules/models_settings.py
index 5efde34..2ed658b 100644
--- a/modules/models_settings.py
+++ b/modules/models_settings.py
@@ -24,9 +24,9 @@ def infer_loader(model_name):
         loader = None
     elif Path(f'{shared.args.model_dir}/{model_name}/quantize_config.json').exists() or ('wbits' in model_settings and type(model_settings['wbits']) is int and model_settings['wbits'] > 0):
         loader = 'AutoGPTQ'
-    elif len(list(path_to_model.glob('*ggml*.bin'))) > 0:
+    elif len(list(path_to_model.glob('*.gguf*'))) > 0:
         loader = 'llama.cpp'
-    elif re.match(r'.*ggml.*\.bin', model_name.lower()):
+    elif re.match(r'.*\.gguf', model_name.lower()):
         loader = 'llama.cpp'
     elif re.match(r'.*rwkv.*\.pth', model_name.lower()):
         loader = 'RWKV'