vbatts/llama.cpp
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convert_lora : fix default filename

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The default filename was previously hardcoded.

* convert_hf : Model.fname_out can no longer be None
This commit is contained in:
Francis Couture-Harpin 2024-07-20 16:40:58 -04:00
parent a3d154b260
commit bf8e71b0c0
4 changed files with 35 additions and 31 deletions
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19
gguf-py/gguf/metadata.py
View file

@ -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_path = model_path
model_card = Metadata.load_model_card(model_card_path)
model_card = Metadata.load_model_card(model_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):
name_types[i].add("finetune")
if part.lower() == "lora":
name_parts[i] = "LoRA"
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")
# 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:

9
gguf-py/tests/test_metadata.py
View file

@ -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'],