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updated release notes, small fix
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doc/changes/unreleased.md

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#### BREAKING CHANGES:
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* The `max_length` parameter has been renamed to `max_new_tokens`, and its behavior changed.
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Both of these changes where done in accordance with changes in [transformers](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.TextGenerationPipeline).
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* All prediction udf's have been renamed:
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| Old UDF name | new UDF name |
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|--------------------------------------------|-----------------------------|
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| TE_FILLING_MASK_UDF | AI_FILL_MASK_EXTENDED |
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| TE_QUESTION_ANSWERING_UDF | AI_ANSWER_EXTENDED |
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| TE_SEQUENCE_CLASSIFICATION_SINGLE_TEXT_UDF | AI_CUSTOM_CLASSIFY_EXTENDED |
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| TE_SEQUENCE_CLASSIFICATION_TEXT_PAIR_UDF | AI_ENTAILMENT_EXTENDED |
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| TE_TEXT_GENERATION_UDF | AI_COMPLETE_EXTENDED |
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| TE_TRANSLATION_UDF | AI_TRANSLATE_EXTENDED |
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| TE_TOKEN_CLASSIFICATION_UDF | AI_EXTRACT_EXTENDED |
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| TE_ZERO_SHOT_CLASSIFICATION_UDF | AI_CLASSIFY_EXTENDED |
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## Features
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## Bugfixes
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* #343: Fixed max_length parameter being ignored, renamed max_length to max_new_tokens
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* #343: Fixed max_length parameter being ignored, renamed max_length to
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## Documentation
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* #346: Changed translation_udf unit tests to use StandaloneUdfMock
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* #323: Standardized udf parameter order (changes in TE_DELETE_MODEL_UDF, TE_MODEL_DOWNLOADER_UDF)
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* #350: Renamed all prediction udf's.
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## Security
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doc/user_guide/manage_models.md

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Some models can be used for multiple types of tasks, but Hugging Face Transformers stores different metadata depending on the task of the model, which affects how the model is loaded later. Setting an incorrect task type, or leaving the task type empty may affect the models performance severely.
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Available task types are the same as the names of our available UDFs, namely:
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Available task types are:
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* `filling_mask`
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* `question_answering`
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* `sequence_classification`

test/integration_tests/with_db/udfs/test_ai_answer_extended_script.py

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def test_ai_answer_extended_script(
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setup_database, db_conn, upload_ai_answer_model_to_bucketfs
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setup_database, db_conn, upload_question_answering_model_to_bucketfs
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):
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bucketfs_conn_name, _ = setup_database
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question = "Where is Exasol based?"

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