Update transformers requirement from <2.5.0,>=2.4.0 to >=2.4.0,<2.8.0

[dependabot-preview]

Updates the requirements on transformers to permit the latest version.

Release notes

Sourced from transformers's releases.

T5 Model, BART summarization example and reduced memory, translation pipeline

T5 Model (@patrickvonplaten, @thomwolf )

T5 is a powerful encoder-decoder model that formats every NLP problem into a text-to-text format. It achieves state of the art results on a variety of NLP tasks (Summarization, Question-Answering, ...).

Five sets of pre-trained weights (pre-trained on a multi-task mixture of unsupervised and supervised tasks) are released. In ascending order from 60 million parameters to 11 billion parameters:

t5-small, t5-base, t5-large, t5-3b, t5-11b

T5 can now be used with the translation and summarization pipeline.

Related:

• paper
• official code
• model available in Hugging Face's community models
• docs

Big thanks to the original authors, especially @craffel who helped answer our questions, reviewed PRs and tested T5 extensively.

New BART checkpoint: bart-large-xsum (@sshleifer)

These weights are from BART finetuned on the XSum abstractive summarization challenge, which encourages shorter (more abstractive) summaries. It achieves state of the art.

BART summarization example with pytorch-lightning (@acarrera94)

New example: BART for summarization, using Pytorch-lightning. Trains on CNN/DM and evaluates.

Translation pipeline (@patrickvonplaten)

A new pipeline is available, leveraging the T5 model. The T5 model was added to the summarization pipeline as well.

Memory improvements with BART (@sshleifer)

In an effort to have the same memory footprint and same computing power necessary to run inference on BART, several improvements have been made on the model:

• Remove the LM head and use the embedding matrix instead (~200MB)
• Call encoder before expanding input_ids (~1GB)
• SelfAttention only returns weights if config.output_attentions (~500MB)
• Two separate, smaller decoder attention masks (~500MB)
• drop columns that are exclusively pad_token_id from input_ids in evaluate_cnn example.

New model: XLMForTokenClassification (@sakares)

A new head was added to XLM: XLMForTokenClassification.

Commits

• 6f5a12a Release: v2.7.0
• 296252c fix lm lables in docstring (#3529)
• 75ec6c9 [T5] make decoder input ids optional for t5 training (#3521)
• 5b44e0a [T5] Add training documenation (#3507)
• 33ef700 [Docs] examples/summarization/bart: Simplify CNN/DM preprocessi… (#3516)
• f6a23d1 [BART] add bart-large-xsum weights (#3422)
• 601ac5b [model_cards]: use MIT license for all dbmdz models
• 17dceae Fix circle ci flaky fail of wmt example (#3485)
• 00ea100 add summarization and translation to notebook (#3478)
• b08259a run_ner.py / bert-base-multilingual-cased can output empty tokens (#2991)
• 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)

[dirkgr]

Closed in favor of #4018.

[dependabot-preview]

OK, I won't notify you again about this release, but will get in touch when a new version is available. If you'd rather skip all updates until the next major or minor version, let me know by commenting @dependabot ignore this major version or @dependabot ignore this minor version.

If you change your mind, just re-open this PR and I'll resolve any conflicts on it.