Add parametrized Transformers smoke test for tokenizer robustness#1814
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RobinPicard merged 2 commits intodottxt-ai:mainfrom Feb 2, 2026
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Almost there! Thanks for your perseverance!
tests/models/test_transformers.py
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| hf_tokenizer = transformers.AutoTokenizer.from_pretrained(model_name) | ||
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| if hf_tokenizer.pad_token is None: |
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To me it's the purpose of this test to fail if something is wrong in that domain. If adjustments like that must be made for some tokenizers/models, it should live in the library
tests/models/test_transformers.py
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| constraint, | ||
| max_new_tokens=5, | ||
| do_sample=False, |
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I don't think it makes sense to loop if we then use do_sample=False
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Thanks for the clarification @RobinPicard - I’ve removed the tokenizer padding adjustment from the test and simplified it to a single deterministic run. Pushed an update. |
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This PR replays the parametrized Transformers smoke test cleanly on top of
main.It keeps the test in
test_transformers.py, avoids anyconftest.pychanges, and exercises tokenizer differences usingTEST_MODELplus a small secondary model.Supersedes #1774.