feat: Allow passing model and tokenizer to ArgillaTrainer directly #3751
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The test failures seem unrelated, all |
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@tomaarsen, we did not but Gabri just mentioned to rerun it. |
Co-authored-by: David Berenstein <david.m.berenstein@gmail.com>
Also removed tokenizer from setfit (where it didn't do anything) and updated some docstrings
…illa-io/argilla into feat/trainer_model_tokenizer
Codecov ReportPatch coverage is 📢 Thoughts on this report? Let us know!. |
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The URL of the deployed environment for this PR is https://argilla-quickstart-pr-3751-ki24f765kq-no.a.run.app |
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tomaarsen
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Oct 11, 2023
Hello! # Argilla Community Growers Ever since #3751, `model` can also be an already initialized model. This edge case was being missed before. This should help with the test failures on #3911. **Type of change** (Please delete options that are not relevant. Remember to title the PR according to the type of change) - [x] Bug fix (non-breaking change which fixes an issue) - [ ] New feature (non-breaking change which adds functionality) - [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected) - [ ] Refactor (change restructuring the codebase without changing functionality) - [ ] Improvement (change adding some improvement to an existing functionality) - [ ] Documentation update **How Has This Been Tested** `pytest .\tests\integration\client\feedback\training\test_trainer.py::test_argilla_trainer_text_classification_with_model_tokenizer` **Checklist** - [ ] I added relevant documentation - [ ] follows the style guidelines of this project - [x] I did a self-review of my code - [ ] I made corresponding changes to the documentation - [ ] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I filled out [the contributor form](https://tally.so/r/n9XrxK) (see text above) - [ ] I have added relevant notes to the CHANGELOG.md file (See https://keepachangelog.com/) --- - Tom Aarsen
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Hello!
Description
Closes #3631.
This is important to give users freedom to very specifically set up their tokenizer. This is required e.g. for SFT with TRL.
Type of change
How Has This Been Tested
Updated the relevant tests (TRL, Transformers) to also train with the passed model & tokenizer.
Checklist
CHANGELOG.mdfile (See https://keepachangelog.com/)TODO: