Skip to content
This repository has been archived by the owner on Dec 16, 2022. It is now read-only.

Update transformers requirement from <2.5.0,>=2.4.0 to >=2.4.0,<2.7.0 #3984

Conversation

dependabot-preview[bot]
Copy link
Contributor

Updates the requirements on transformers to permit the latest version.

Release notes

Sourced from transformers's releases.

BART, organizations, community notebooks, lightning examples, dropping Python 3.5

New Model: BART (added by @sshleifer)

Bart is one of the first Seq2Seq models in the library, and achieves state of the art results on text generation tasks, like abstractive summarization. Three sets of pretrained weights are released:

  • bart-large: the pretrained base model
  • bart-large-cnn: the base model finetuned on the CNN/Daily Mail Abstractive Summarization Task
  • bart-large-mnli: the base model finetuned on the MNLI classification task.

Related:

Big thanks to the original authors, especially Mike Lewis, Yinhan Liu, Naman Goyal who helped answer our questions.

Model sharing CLI: support for organizations

The huggingface API for model upload now supports organisations.

Notebooks (@mfuntowicz)

A few beginner-oriented notebooks were added to the library, aiming at demystifying the two libraries huggingface/transformers and huggingface/tokenizers. Contributors are welcome to contribute links to their notebooks as well.

pytorch-lightning examples (@srush)

Examples leveraging pytorch-lightning were added, led by @srush. The first example that was added is the NER example. The second example is a lightning GLUE example, added by @nateraw.

New model architectures: CamembertForQuestionAnswering,

  • CamembertForQuestionAnswering was added to the library and to the SQuAD script @maximeilluin
  • AlbertForTokenClassification was added to the library and to the NER example @marma

Multiple fixes were done on the fast tokenizers to make them entirely compatible with the python tokenizers (@mfuntowicz)

Most of these fixes were done in the patch 2.5.1. Fast tokenizers should now have the exact same API as the python ones, with some additional functionalities.

Docker images (@mfuntowicz)

Docker images for transformers were added.

Generation overhaul (@patrickvonplaten)

  • Special token IDs logic were improved in run_generation and in corresponding tests.
  • Slow tests for generation were added for pre-trained LM models
  • Greedy generation when doing beam search
  • Sampling when doing beam search
... (truncated)
Commits
  • fbc5bf1 v2.6.0 release: isort un-pinned
  • b88bda6 Add right model and tokenizer path in example
  • b31ef22 [model_cards] 🇹🇷 Add new (uncased, 128k) BERTurk model
  • b4009cb [model_cards] 🇹🇷 Add new (cased, 128k) BERTurk model
  • d328349 [model_cards] 🇹🇷 Add new (uncased) BERTurk model
  • e279a31 Model cards for CS224n SQuAD2.0 models (#3406)
  • 7372e62 Added precisions in SciBERT-NLI model card (#3410)
  • 471cce2 Release: v2.6.0
  • e392ba6 Add camembert integration tests (#3375)
  • a8e3336 [examples] Use AutoModels in more examples
  • Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

  • @dependabot rebase will rebase this PR
  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot merge will merge this PR after your CI passes on it
  • @dependabot squash and merge will squash and merge this PR after your CI passes on it
  • @dependabot cancel merge will cancel a previously requested merge and block automerging
  • @dependabot reopen will reopen this PR if it is closed
  • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
  • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
  • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
  • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
  • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language
  • @dependabot badge me will comment on this PR with code to add a "Dependabot enabled" badge to your readme

Additionally, you can set the following in your Dependabot dashboard:

  • Update frequency (including time of day and day of week)
  • Pull request limits (per update run and/or open at any time)
  • Out-of-range updates (receive only lockfile updates, if desired)
  • Security updates (receive only security updates, if desired)

@dependabot-preview dependabot-preview bot added the dependencies Pull requests that update a dependency file label Mar 25, 2020
@dependabot-preview
Copy link
Contributor Author

Superseded by #4003.

@dependabot-preview dependabot-preview bot deleted the dependabot/pip/transformers-gte-2.4.0-and-lt-2.7.0 branch March 30, 2020 13:24
Sign up for free to subscribe to this conversation on GitHub. Already have an account? Sign in.
Labels
dependencies Pull requests that update a dependency file
Projects
None yet
Development

Successfully merging this pull request may close these issues.

0 participants