onnx_diagnostic.torch_models.hghub.hub_api

onnx_diagnostic.torch_models.hghub.hub_api.enumerate_model_list(n: int = 50, task: str | None = None, library: str | None = None, tags: str | List[str] | None = None, search: str | None = None, dump: str | None = None, filter: str | None = None, verbose: int = 0)

Enumerates models coming from huggingface_hub.

Parameters:

• n – number of models to retrieve (-1 for all)

• task – see huggingface_hub.HfApi.list_models()

• tags – see huggingface_hub.HfApi.list_models()

• library – see huggingface_hub.HfApi.list_models()

• search – see huggingface_hub.HfApi.list_models()

• filter – see huggingface_hub.HfApi.list_models()

• dump – dumps the result in this csv file

• verbose – show progress

onnx_diagnostic.torch_models.hghub.hub_api.get_architecture_default_values(architecture: str)

The configuration may miss information to build the dummy inputs. This information returns the missing pieces.

onnx_diagnostic.torch_models.hghub.hub_api.get_cached_configuration(name: str, **kwargs) → PretrainedConfig | None

Returns cached configuration to avoid having to many accesses to internet. It returns None if not Cache. The list of cached models follows.

    ['HuggingFaceM4/tiny-random-idefics',
     'Intel/bert-base-uncased-mrpc',
     'Xenova/tiny-random-Phi3ForCausalLM',
     'arnir0/Tiny-LLM',
     'echarlaix/tiny-random-PhiForCausalLM',
     'echarlaix/tiny-random-mistral',
     'facebook/bart-base',
     'facebook/bart-large-cnn',
     'fxmarty/pix2struct-tiny-random',
     'fxmarty/tiny-dummy-qwen2',
     'fxmarty/tiny-llama-fast-tokenizer',
     'fxmarty/tiny-random-GemmaForCausalLM',
     'google-bert/bert-base-multilingual-cased',
     'hf-internal-testing/tiny-random-BeitForImageClassification',
     'hf-internal-testing/tiny-random-GPTNeoXForCausalLM',
     'hf-internal-testing/tiny-random-GraniteForCausalLM',
     'hf-internal-testing/tiny-random-HieraForImageClassification',
     'hf-internal-testing/tiny-random-MaskFormerForInstanceSegmentation',
     'hf-internal-testing/tiny-random-MoonshineForConditionalGeneration',
     'hf-internal-testing/tiny-random-Olmo2ForCausalLM',
     'hf-internal-testing/tiny-random-OlmoForCausalLM',
     'hf-internal-testing/tiny-random-ViTMSNForImageClassification',
     'hf-internal-testing/tiny-random-YolosModel',
     'hf-internal-testing/tiny-random-convnext',
     'hf-internal-testing/tiny-random-mobilevit',
     'hf-internal-testing/tiny-xlm-roberta',
     'hf-tiny-model-private/tiny-random-PLBartForConditionalGeneration',
     'hustvl/yolos-tiny',
     'microsoft/phi-2',
     'openai/clip-vit-base-patch16',
     'openai/whisper-tiny',
     'sentence-transformers/all-MiniLM-L6-v1',
     'sshleifer/tiny-marian-en-de',
     'tiiuae/falcon-mamba-tiny-dev']

onnx_diagnostic.torch_models.hghub.hub_api.get_model_info(model_id) → Any

Returns the model info for a model_id.

onnx_diagnostic.torch_models.hghub.hub_api.get_pretrained_config(model_id: str, trust_remote_code: bool = True, use_preinstalled: bool = True, subfolder: str | None = None, **kwargs) → Any

Returns the config for a model_id.

Parameters:

• model_id – model id

• trust_remote_code – trust_remote_code, see transformers.AutoConfig.from_pretrained()

• use_preinstalled – if use_preinstalled, uses this version to avoid accessing the network, if available, it is returned by get_cached_configuration(), the cached list is mostly for unit tests

• subfolder – subfolder for the given model id

• kwargs – additional kwargs

Returns:

a configuration

onnx_diagnostic.torch_models.hghub.hub_api.task_from_arch(arch: str, default_value: str | None = None) → str

This function relies on stored information. That information needs to be refresh.

Parameters:

• arch – architecture name

• default_value – default value in case the task cannot be determined

Returns:

task

    last refresh 2025-03-26

List of supported architectures, see load_architecture_task.

onnx_diagnostic.torch_models.hghub.hub_api.task_from_id(model_id: str, default_value: str | None = None, pretrained: bool = False, fall_back_to_pretrained: bool = True) → str

Returns the task attached to a model id.

Parameters:

• model_id – model id

• default_value – if specified, the function returns this value if the task cannot be determined

• pretrained – uses the config

• fall_back_to_pretrained – falls back to pretrained config

Returns:

task

onnx_diagnostic.torch_models.hghub.hub_api.task_from_tags(tags: str | List[str]) → str

Guesses the task from the list of tags. If given by a string, | should be the separator.