convert_lora : fix default filename

The default filename was previously hardcoded.

* convert_hf : Model.fname_out can no longer be None

convert_hf_to_gguf.py

@@ -48,7 +48,7 @@ class Model:
 
     dir_model: Path
     ftype: gguf.LlamaFileType
-    fname_out: Path | None
+    fname_out: Path
     is_big_endian: bool
     endianess: gguf.GGUFEndian
     use_temp_file: bool
@@ -67,7 +67,7 @@ class Model:
     # subclasses should define this!
     model_arch: gguf.MODEL_ARCH
 
-    def __init__(self, dir_model: Path, ftype: gguf.LlamaFileType, fname_out: Path | None, is_big_endian: bool = False,
+    def __init__(self, dir_model: Path, ftype: gguf.LlamaFileType, fname_out: Path, is_big_endian: bool = False,
                  use_temp_file: bool = False, eager: bool = False,
                  metadata_override: Path | None = None, model_name: str | None = None,
                  split_max_tensors: int = 0, split_max_size: int = 0, dry_run: bool = False, small_first_shard: bool = False):
@@ -347,7 +347,7 @@ class Model:
 
         total_params, shared_params, expert_params, expert_count = self.gguf_writer.get_total_parameter_count()
 
-        self.metadata = gguf.Metadata.load(self.metadata_override, self.dir_model, self.model_name, self.dir_model_card, total_params)
+        self.metadata = gguf.Metadata.load(self.metadata_override, self.dir_model_card, self.model_name, total_params)
 
         # Fallback to model directory name if metadata name is still missing
         if self.metadata.name is None:
@@ -361,27 +361,22 @@ class Model:
         output_type: str = self.ftype.name.partition("_")[2]
 
         # Filename Output
-        # Note: `not is_dir()` is used because `.is_file()` will not detect
+        if self.fname_out.is_dir():
-        #       file template strings as it doesn't actually exist as a file
-        if self.fname_out is not None and not self.fname_out.is_dir():
-            # Output path is a custom defined templated filename
-
-            # Process templated file name with the output ftype, useful with the "auto" ftype
-            self.fname_out = self.fname_out.parent / gguf.fill_templated_filename(self.fname_out.name, output_type)
-        else:
             # Generate default filename based on model specification and available metadata
             if not vocab_only:
                 fname_default: str = gguf.naming_convention(self.metadata.name, self.metadata.basename, self.metadata.finetune, self.metadata.version, self.metadata.size_label, output_type, model_type="LoRA" if total_params < 0 else None)
             else:
                 fname_default: str = gguf.naming_convention(self.metadata.name, self.metadata.basename, self.metadata.finetune, self.metadata.version, size_label=None, output_type=None, model_type="vocab")
 
-            # Check if preferred output directory path was provided
+            # Use the default filename
-            if self.fname_out is not None and self.fname_out.is_dir():
-                # output path is a directory
             self.fname_out = self.fname_out / f"{fname_default}.gguf"
         else:
-                # output in the same directory as the model by default
+            # Output path is a custom defined templated filename
-                self.fname_out = self.dir_model / f"{fname_default}.gguf"
+            # Note: `not is_dir()` is used because `.is_file()` will not detect
+            #       file template strings as it doesn't actually exist as a file
+
+            # Process templated file name with the output ftype, useful with the "auto" ftype
+            self.fname_out = self.fname_out.parent / gguf.fill_templated_filename(self.fname_out.name, output_type)
 
         self.set_type()
 
@@ -3626,10 +3621,10 @@ def main() -> None:
         logger.error("Error: Cannot use temp file when splitting")
         sys.exit(1)
 
-    fname_out = None
-
     if args.outfile is not None:
         fname_out = args.outfile
+    else:
+        fname_out = dir_model
 
     logger.info(f"Loading model: {dir_model.name}")
 
@@ -3660,7 +3655,6 @@ def main() -> None:
         else:
             logger.info("Exporting model...")
             model_instance.write()
-            assert model_instance.fname_out is not None
             out_path = f"{model_instance.fname_out.parent}{os.sep}" if is_split else model_instance.fname_out
             logger.info(f"Model successfully exported to {out_path}")
 

convert_lora_to_gguf.py

@@ -290,7 +290,7 @@ if __name__ == '__main__':
         fname_out = args.outfile
     else:
         # output in the same directory as the model by default
-        fname_out = dir_lora / 'ggml-lora-{ftype}.gguf'
+        fname_out = dir_lora
 
     if os.path.exists(input_model):
         # lazy import load_file only if lora is in safetensors format.

gguf-py/gguf/metadata.py

@@ -44,7 +44,7 @@ class Metadata:
     datasets: Optional[list[str]] = None
 
     @staticmethod
-    def load(metadata_override_path: Optional[Path] = None, model_path: Optional[Path] = None, model_name: Optional[str] = None, model_card_path: Optional[Path] = None, total_params: int = 0) -> Metadata:
+    def load(metadata_override_path: Optional[Path] = None, model_path: Optional[Path] = None, model_name: Optional[str] = None, total_params: int = 0) -> Metadata:
         # This grabs as many contextual authorship metadata as possible from the model repository
         # making any conversion as required to match the gguf kv store metadata format
         # as well as giving users the ability to override any authorship metadata that may be incorrect
@@ -52,14 +52,12 @@ class Metadata:
         # Create a new Metadata instance
         metadata = Metadata()
 
-        if model_card_path is None:
+        model_card = Metadata.load_model_card(model_path)
-            model_card_path = model_path
-
-        model_card = Metadata.load_model_card(model_card_path)
         hf_params = Metadata.load_hf_parameters(model_path)
+        # TODO: load adapter_config.json when possible, it usually contains the base model of the LoRA adapter
 
         # heuristics
-        metadata = Metadata.apply_metadata_heuristic(metadata, model_card, hf_params, model_card_path, total_params)
+        metadata = Metadata.apply_metadata_heuristic(metadata, model_card, hf_params, model_path, total_params)
 
         # Metadata Override File Provided
         # This is based on LLM_KV_NAMES mapping in llama.cpp
@@ -232,11 +230,14 @@ class Metadata:
                 name_parts[i] = part
             # Some easy to recognize finetune names
             elif i > 0 and re.fullmatch(r'chat|instruct|vision|lora', part, re.IGNORECASE):
+                if total_params < 0 and part.lower() == "lora":
+                    # ignore redundant "lora" in the finetune part when the output is a lora adapter
+                    name_types[i].add("type")
+                else:
                     name_types[i].add("finetune")
-                if part.lower() == "lora":
-                    name_parts[i] = "LoRA"
 
         # Ignore word-based size labels when there is at least a number-based one present
+        # TODO: should word-based size labels always be removed instead?
         if any(c.isdecimal() for n, t in zip(name_parts, name_types) if "size_label" in t for c in n):
             for n, t in zip(name_parts, name_types):
                 if "size_label" in t:

gguf-py/tests/test_metadata.py

@@ -159,6 +159,15 @@ class TestMetadataMethod(unittest.TestCase):
         self.assertEqual(gguf.Metadata.get_model_id_components("mistralai/-Mistral--Nemo-Base-2407-"),
                          ('-Mistral--Nemo-Base-2407-', 'mistralai', 'Mistral-Nemo-Base', None, '2407', None))
 
+        ## LoRA ##
+
+        self.assertEqual(gguf.Metadata.get_model_id_components("Llama-3-Instruct-abliteration-LoRA-8B"),
+                         ('Llama-3-Instruct-abliteration-LoRA-8B', None, 'Llama-3', 'Instruct-abliteration-LoRA', None, '8B'))
+
+        # Negative size --> output is a LoRA adaper --> prune "LoRA" out of the name to avoid redundancy with the suffix
+        self.assertEqual(gguf.Metadata.get_model_id_components("Llama-3-Instruct-abliteration-LoRA-8B", -1234),
+                         ('Llama-3-Instruct-abliteration-LoRA-8B', None, 'Llama-3', 'Instruct-abliteration', None, '8B'))
+
     def test_apply_metadata_heuristic_from_model_card(self):
         model_card = {
             'tags': ['Llama-3', 'instruct', 'finetune', 'chatml', 'DPO', 'RLHF', 'gpt4', 'synthetic data', 'distillation', 'function calling', 'json mode', 'axolotl'],