vbatts/llama.cpp
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convert-*.py: add heuristic to directory name fallback

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Also add source_url for huggingface url
This commit is contained in:
brian khuu 2024-06-04 02:25:11 +10:00
parent 39472a09da
commit 3625a42061
5 changed files with 57 additions and 33 deletions
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4
convert_hf_to_gguf.py
View file

@ -146,7 +146,7 @@ class Model:
self.fname_out = fname_out.parent / gguf.fill_templated_filename(fname_out.name, output_type) self.fname_out = fname_out.parent / gguf.fill_templated_filename(fname_out.name, output_type)
else: else:
# output in the same directory as the model by default # output in the same directory as the model by default
self.fname_out = dir_model.parent / self.fname_default self.fname_out = dir_model / f"{self.fname_default}.gguf"
# Configure GGUF Writer # Configure GGUF Writer
self.gguf_writer = gguf.GGUFWriter(self.fname_out, gguf.MODEL_ARCH_NAMES[self.model_arch], endianess=self.endianess, use_temp_file=self.use_temp_file) self.gguf_writer = gguf.GGUFWriter(self.fname_out, gguf.MODEL_ARCH_NAMES[self.model_arch], endianess=self.endianess, use_temp_file=self.use_temp_file)
@ -447,7 +447,7 @@ class Model:
sum_weight_estimate += sum_weights_in_tensor sum_weight_estimate += sum_weights_in_tensor
# Calculate weight estimate per model # Calculate weight estimate per model
per_model_weight_estimate = (sum_weight_estimate / expert_count) if (expert_count > 0) else sum_weight_estimate per_model_weight_estimate = (sum_weight_estimate / expert_count) if expert_count is not None and (expert_count > 0) else sum_weight_estimate
return per_model_weight_estimate return per_model_weight_estimate

16
examples/convert_legacy_llama.py
View file

@ -806,11 +806,11 @@ class OutputFile:
if metadata.source_hf_repo is not None: if metadata.source_hf_repo is not None:
self.gguf.add_source_hf_repo(metadata.source_hf_repo) self.gguf.add_source_hf_repo(metadata.source_hf_repo)
if metadata.tags is not None: if metadata.tags is not None:
self.gguf_writer.add_tags(metadata.tags) self.gguf.add_tags(metadata.tags)
if metadata.languages is not None: if metadata.languages is not None:
self.gguf_writer.add_languages(metadata.languages) self.gguf.add_languages(metadata.languages)
if metadata.datasets is not None: if metadata.datasets is not None:
self.gguf_writer.add_datasets(metadata.datasets) self.gguf.add_datasets(metadata.datasets)
def add_meta_arch(self, params: Params) -> None: def add_meta_arch(self, params: Params) -> None:
# Metadata About The Neural Architecture Itself # Metadata About The Neural Architecture Itself
@ -961,6 +961,8 @@ class OutputFile:
of = OutputFile(fname_out, endianess=endianess) of = OutputFile(fname_out, endianess=endianess)
print(metadata)
# meta data # meta data
of.add_meta_model(params, metadata) of.add_meta_model(params, metadata)
of.add_meta_arch(params) of.add_meta_arch(params)
@ -1017,7 +1019,7 @@ def per_model_weight_count_estimation(tensors: dict[str, LazyTensor], expert_cou
sum_weight_estimate += sum_weights_in_tensor sum_weight_estimate += sum_weights_in_tensor
# Calculate weight estimate per model # Calculate weight estimate per model
per_model_weight_estimate = (sum_weight_estimate / expert_count) if (expert_count > 0) else sum_weight_estimate per_model_weight_estimate = (sum_weight_estimate / expert_count) if expert_count is not None and (expert_count > 0) else sum_weight_estimate
return per_model_weight_estimate return per_model_weight_estimate
@ -1302,9 +1304,6 @@ def main(args_in: list[str] | None = None) -> None:
else: else:
model_plus = ModelPlus(model = {}, paths = [dir_model / 'dummy'], format = 'none', vocab = None) model_plus = ModelPlus(model = {}, paths = [dir_model / 'dummy'], format = 'none', vocab = None)
model_params_count = per_model_weight_count_estimation(model_plus.model.items(), params.n_experts)
logger.info(f"model parameters count : {model_params_count} ({gguf.model_weight_count_rounded_notation(model_params_count)})")
if args.dump: if args.dump:
do_dump_model(model_plus) do_dump_model(model_plus)
return return
@ -1370,6 +1369,9 @@ def main(args_in: list[str] | None = None) -> None:
if metadata.name is None: if metadata.name is None:
metadata.name = params.path_model.name metadata.name = params.path_model.name
model_params_count = per_model_weight_count_estimation(model_plus.model.items(), params.n_experts)
logger.info(f"model parameters count : {model_params_count} ({gguf.model_weight_count_rounded_notation(model_params_count)})")
logger.info(f"Vocab info: {vocab}") logger.info(f"Vocab info: {vocab}")
logger.info(f"Special vocab info: {special_vocab}") logger.info(f"Special vocab info: {special_vocab}")
model = model_plus.model model = model_plus.model

6
gguf-py/gguf/gguf_writer.py
View file

@ -482,13 +482,13 @@ class GGUFWriter:
self.add_string(Keys.General.PARAMETER_WEIGHT_CLASS, parameter_weight_class) self.add_string(Keys.General.PARAMETER_WEIGHT_CLASS, parameter_weight_class)
def add_tags(self, tags: Sequence[str]) -> None: def add_tags(self, tags: Sequence[str]) -> None:
self.add_array(Keys.Tokenizer.TAGS, tags) self.add_array(Keys.General.TAGS, tags)
def add_languages(self, languages: Sequence[str]) -> None: def add_languages(self, languages: Sequence[str]) -> None:
self.add_array(Keys.Tokenizer.LANGUAGES, languages) self.add_array(Keys.General.LANGUAGES, languages)
def add_datasets(self, datasets: Sequence[str]) -> None: def add_datasets(self, datasets: Sequence[str]) -> None:
self.add_array(Keys.Tokenizer.DATASETS, datasets) self.add_array(Keys.General.DATASETS, datasets)
def add_name(self, name: str) -> None: def add_name(self, name: str) -> None:
self.add_string(Keys.General.NAME, name) self.add_string(Keys.General.NAME, name)

63
gguf-py/gguf/metadata.py
View file

@ -51,21 +51,28 @@ class Metadata:
metadata.name = model_card.get("model_name") metadata.name = model_card.get("model_name")
if "base_model" in model_card: if "base_model" in model_card:
# Example: stabilityai/stable-diffusion-xl-base-1.0. Can also be a list (for merges)
model_id = model_card.get("base_model") model_id = model_card.get("base_model")
model_name_normal, organization_name, base_name, fine_tune, version_string, parameter_weight_class = Metadata.get_model_name_components(model_id)
if metadata.name is None and model_name_normal is not None: # Check if string. We cannot handle lists as that is too ambagious
metadata.name = model_name_normal if isinstance(model_id, str):
if metadata.organization is None and organization_name is not None: model_name_normal, organization_name, base_name, fine_tune, version_string, parameter_weight_class = Metadata.get_model_name_components(model_id)
metadata.organization = organization_name if metadata.name is None and model_name_normal is not None:
if metadata.basename is None and base_name is not None: metadata.name = model_name_normal
metadata.basename = base_name if metadata.organization is None and organization_name is not None:
if metadata.finetune is None and fine_tune is not None: metadata.organization = organization_name
metadata.finetune = fine_tune if metadata.basename is None and base_name is not None:
if metadata.version is None and version_string is not None: metadata.basename = base_name
metadata.version = version_string if metadata.finetune is None and fine_tune is not None:
if metadata.parameter_weight_class is None and parameter_weight_class is not None: metadata.finetune = fine_tune
metadata.parameter_weight_class = parameter_weight_class if metadata.version is None and version_string is not None:
metadata.version = version_string
if metadata.parameter_weight_class is None and parameter_weight_class is not None:
metadata.parameter_weight_class = parameter_weight_class
if metadata.source_url is None:
metadata.source_url = f"https://huggingface.co/{model_id}"
if metadata.source_hf_repo is None:
metadata.source_hf_repo = model_id
if "model-index" in model_card and len(model_card["model_name"]) == 1 and "name" in model_card["model_name"][0]: if "model-index" in model_card and len(model_card["model_name"]) == 1 and "name" in model_card["model_name"][0]:
# This is a model index which has model id that can be extracted into organization and model name # This is a model index which has model id that can be extracted into organization and model name
@ -100,11 +107,11 @@ class Metadata:
# non huggingface model card standard but notice some model creator using it # non huggingface model card standard but notice some model creator using it
metadata.author = model_card.get("model_creator") metadata.author = model_card.get("model_creator")
if metadata.tags is None: if metadata.tags is None:
metadata.tags = model_card.get("tags", []) metadata.tags = model_card.get("tags", None)
if metadata.languages is None: if metadata.languages is None:
metadata.languages = model_card.get("language", model_card.get("languages", [])) metadata.languages = model_card.get("language", model_card.get("languages", None))
if metadata.datasets is None: if metadata.datasets is None:
metadata.datasets = model_card.get("datasets", model_card.get("dataset", [])) metadata.datasets = model_card.get("datasets", model_card.get("dataset", None))
# load huggingface parameters if available # load huggingface parameters if available
hf_params = Metadata.load_huggingface_parameters(model_path) hf_params = Metadata.load_huggingface_parameters(model_path)
@ -126,14 +133,28 @@ class Metadata:
metadata.version = version_string metadata.version = version_string
if metadata.parameter_weight_class is None and parameter_weight_class is not None: if metadata.parameter_weight_class is None and parameter_weight_class is not None:
metadata.parameter_weight_class = parameter_weight_class metadata.parameter_weight_class = parameter_weight_class
if metadata.source_hf_repo is None and not Metadata.is_model_name_only(hf_name_or_path): if not Metadata.is_model_name_only(hf_name_or_path):
# Can't just have the model name as the source hf repo as a link to the huggingface website needs the org name and the model name # Can't just have the model name as the source hf repo as a link to the huggingface website needs the org name and the model name
metadata.source_hf_repo = "https://huggingface.co/{hf_name_or_path}" if metadata.source_url is None:
metadata.source_url = f"https://huggingface.co/{hf_name_or_path}"
if metadata.source_hf_repo is None:
metadata.source_hf_repo = hf_name_or_path
# Use Directory Folder Name As Fallback Name # Use Directory Folder Name As Fallback Name
if metadata.name is None: if model_path is not None and model_path.exists():
if model_path is not None and model_path.exists(): model_name_normal, organization_name, base_name, fine_tune, version_string, parameter_weight_class = Metadata.get_model_name_components(model_path.name)
metadata.name = model_path.name if metadata.name is None and model_name_normal is not None:
metadata.name = model_name_normal
if metadata.organization is None and organization_name is not None:
metadata.organization = organization_name
if metadata.basename is None and base_name is not None:
metadata.basename = base_name
if metadata.finetune is None and fine_tune is not None:
metadata.finetune = fine_tune
if metadata.version is None and version_string is not None:
metadata.version = version_string
if metadata.parameter_weight_class is None and parameter_weight_class is not None:
metadata.parameter_weight_class = parameter_weight_class
# Metadata Override File Provided # Metadata Override File Provided
# This is based on LLM_KV_NAMES mapping in llama.cpp # This is based on LLM_KV_NAMES mapping in llama.cpp

1
gguf-py/gguf/utility.py
View file

@ -44,6 +44,7 @@ def parameter_weight_class(expert_count_int:int, model_params_count: int) -> str
return size_class return size_class
def naming_convention(model_name: str, base_name: str, finetune_string:str, version_string:str, parameter_weight_class: str, output_type: str) -> str: def naming_convention(model_name: str, base_name: str, finetune_string:str, version_string:str, parameter_weight_class: str, output_type: str) -> str:
# Reference: https://github.com/ggerganov/ggml/blob/master/docs/gguf.md#gguf-naming-convention # Reference: https://github.com/ggerganov/ggml/blob/master/docs/gguf.md#gguf-naming-convention