v0.0.11: Improved documentation, `hf_hub_download` and `Repository` power-up

v0.0.11: Improved documentation, hf_hub_download and Repository power-up

Improved documentation

The huggingface_hub documentation is now available on hf.co/docs! Additionally, a new step-by-step guide to adding libraries is available.

• New documentation for 🤗 Hub #71 (@osanseviero)
• Step by step guide on adding Model Hub support to libraries #86 (@LysandreJik)

New method: hf_hub_download

A new method is introduced: hf_hub_download. It is the equivalent of doing cached_download(hf_hub_url()), in a single method.

• HF Hub download #137 (@LysandreJik)

Repository power-up

The Repository class is updated to behave more similarly to git. It is now impossible to clone a repository in a folder that already contains files.

The PyTorch Mixin contributed by @vasudevgupta7 is slightly updated to have the push_to_hub method manage a repository as one would from the command line.

• Repository power-up #132 (@LysandreJik)

Improvement & Fixes

• Adding audio-to-audio task. #93 (@Narsil)
• When pipelines fail to load in framework code, for whatever reason #96 (@Narsil)
• Solve rmtree issue on windows #105 (@SBrandeis)
• Add identical_ok option to HfApi.upload_file method #102 (@SBrandeis)
• Solve compatibility issues when calling subprocess.run #104 (@SBrandeis)
• Open source Inference widgets + optimize for community contributions #87 (@julien-c)
• model tags can be undefined #107 (@Pierrci)
• Doc tweaks #109 (@julien-c)
• [huggingface_hub] Support for spaces #108 (@julien-c)
• speechbrain library tag + code snippet #73 (@osanseviero)
• Allow batching for feature-extraction #106 (@osanseviero)
• adding audio-to-audio widget. #95 (@Narsil)
• Add image to text (for image captioning) #114 (@osanseviero)
• Add formatting and upgrade Sentence Transformers api version for better error messages #119 (@osanseviero)
• Change videos in docs so they are played directly in our site #120 (@osanseviero)
• Fix inference API GitHub actions #125 (@osanseviero)
• Fixing sentence-transformers CACHE value for docker + functools (docker needs Py3.8) #123 (@Narsil)
• Load errors with flair should now be generating proper API errors. #121 (@Narsil)
• Simplify manage to autodetect task+framework if possible. #122 (@Narsil)
• Change sentence transformers source to original repo #128 (@osanseviero)
• Allow Python versions with letters in the minor version suffix #82 (@ulf1)
• Update upload_file docs #136 (@LysandreJik)
• Reformat repo README #130 (@osanseviero)
• Add config to model info #135 (@osanseviero)
• Add input validation for structured-data-classification #97 (@osanseviero)

v0.0.10: Merging `huggingface_hub` with `api-inference-community` and hub interfaces

v0.0.10: Merging huggingface_hub with api-inference-community and hub interfaces

v0.0.10 Signs the merging of three components of the HuggingFace stack: the huggingface_hub repository is now the central platform to contribute new libraries to be supported on the hub.

It regroups three previously separated components:

• The huggingface_hub Python library, as the Python library to download, upload, and retrieve information from the hub.
• The api-inference-community, as the platform where libraries wishing for hub support may be added.
• The interfaces, as the definition for pipeline types as well as default widget inputs and definitions/UI elements for third-party libraries.

Future efforts will be focused on further easing contributing third-party libraries to the Hugging Face Hub

Improvement & Fixes

• Add typing extensions to conda yaml file #49 (@LysandreJik)
• Alignment on modelcard metadata specification #39 (@LysandreJik)
• Bring interfaces from widgets-server #50 (@julien-c)
• Sentence similarity default widget and pipeline type #52 (@osanseviero)
• [interfaces] Expose configuration options for external libraries #51 (@julien-c)
• Adding api-inference-community to huggingface_hub. #48 (@Narsil)
• Add TensorFlowTTS as library + code snippet #55 (@osanseviero)
• Add protobuf as a dependency to handle tokenizers that require it: #58 (@Narsil)
• Update validation for NLP tasks #59 (@osanseviero)
• spaCy code snippet and language tag #57 (@osanseviero)
• SpaCy fixes #60 (@osanseviero)
• Allow changing repo visibility programmatically #61 (@osanseviero)
• Add Adapter Transformers snippet #62 (@osanseviero)
• Change order in spaCy snippet #66 (@osanseviero)
• Add validation to check all rows in table question answering have same length #67 (@osanseviero)
• added question-answering part for Bengali language #68 (@sagorbrur)
• Add spaCy to inference API #63 (@osanseviero)
• AllenNLP library tag + code snippet #72 (@osanseviero)
• Fix AllenNLP QA example #80 (@epwalsh)
• do not crash even if this config isn't set #81 (@julien-c)
• Mark model config as optional #83 (@Pierrci)
• Add repr() to ModelFile and RepoObj #75 (@lewtun)
• Refactor create_repo #84 (@SBrandeis)

v0.0.9: HTTP File uploads, multiple filter model selection

v0.0.9: HTTP file uploads, multiple filter model selection

Support for large file uploads

Implementation of an endpoint to programmatically upload (large) files to any repo on the hub, without the need for git, using HTTP POST requests.

• [API] Support for the file upload endpoint #42 (@SBrandeis)

The HfApi.model_list method now allows multiple filters

Models may now be filtered using several filters:

                Example usage:

                    >>> from huggingface_hub import HfApi
                    >>> api = HfApi()

                    >>> # List all models
                    >>> api.list_models()

                    >>> # List only the text classification models
                    >>> api.list_models(filter="text-classification")

                    >>> # List only the russian models compatible with pytorch
                    >>> api.list_models(filter=("ru", "pytorch"))

                    >>> # List only the models trained on the "common_voice" dataset
                    >>> api.list_models(filter="dataset:common_voice")

                    >>> # List only the models from the AllenNLP library
                    >>> api.list_models(filter="allennlp")

• Document the filter argument #41 (@LysandreJik)

ModelInfo now has a readable representation

Improvement of the ModelInfo class so that it displays information about the object.

• Include a readable repr for ModelInfo #32 (@muellerzr)

Improvements and bugfixes

• Fix conda by specifying python version + add tests to main branch #28 (@LysandreJik)
• Improve Mixin #34 (@LysandreJik)
• Enable library_name and library_version in snapshot_download #38 (@LysandreJik)
• [Windows support] Very long filenames #40 (@LysandreJik)
• Make error message more verbose when creating a repo #44 (@osanseviero)
• Open-source /docs #46 (@julien-c)

v0.0.8: Model Info, Snapshot download

• Addition of the HfApi.model_info method to retrieve information about a repo given a revision.
• The accompanying snapshot_download utility to download to cache all files stored in that repo at that given revision.

Example usage of HfApi.model_info:

from huggingface_hub import HfApi

hf_api = HfApi()
model_info = hf_api.model_info("lysandre/dummy-hf-hub")

print("Model ID:", model_info.modelId)

for file in model_info.siblings:
    print("file:", file.rfilename)

outputs:

Model ID: lysandre/dummy-hf-hub
file: .gitattributes
file: README.md

Example usage of snapshot_download:

from huggingface_hub import snapshot_download
import os

repo_path = snapshot_download("lysandre/dummy-hf-hub")
print(os.listdir(repo_path))

outputs:

['.gitattributes', 'README.md']

v0.0.7: Networking improvements + PyTorch mixin

• Networking improvements by @Pierrci and @lhoestq (#21 and #22)

• Adding mixin class for ease saving, uploading, downloading a PyTorch model. See PR #11 by @vasudevgupta7

Example usage:

from huggingface_hub import ModelHubMixin

class MyModel(nn.Module, ModelHubMixin):
   def __init__(self, **kwargs):
      super().__init__()
      self.config = kwargs.pop("config", None)
      self.layer = ...
   def forward(self, ...):
      return ...

model = MyModel()

# saving model to local directory & pushing to hub
model.save_pretrained("mymodel", push_to_hub=True, config={"act": "gelu"})

# initiatizing model & loading it from trained-weights
model = MyModel.from_pretrained("username/mymodel@main")

Thanks a ton for your contributions ♥️

v0.0.6

[Repository] Strip basic auth info

Repository class + other tweaks

v0.0.5

v0.0.5

Repository class

• v0.0.4

Repository helper class to interact with git/git-lfs programmatically

• [Repository] more forgiving lfs_track

• added stderr and exceptions (#19)

  • added stderr and exceptions

  • added log to push and check for commit error

  • fixed quality

  • doc improvements + small tweaks

  • [git_add] actually take input pattern

  • less brittle test if local_dir is an actual git repo

  Co-authored-by: Julien Chaumond julien@huggingface.co

• v0.0.3

Repository helper class to interact with git/git-lfs programmatically

v0.0.3rc2

v0.0.3rc2