About TransformerWordEmbeddings class #2713
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Hey @matirojasg thank you for reporting, @alanakbik as this might be due to my refactoring, I'll look into it soon |
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Awesome, thanks @helpmefindaname! |
helpmefindaname
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alanakbik
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…ulation GH-2713: make transformer offset calculation more robust
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Thank you guys! |
patrickjae
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* flairNLPGH-2632: Revert "Removes hyperparameter features" This reverts commit 9aff426. * flairNLPGH-2632: Updating the param selection docs for the v0.10 syntax * flairNLPGH-2632: Adding hyperopt back to requirements.txt * flairNLPGH-2632: Fixing paramselection code to work with changes in Flair v0.10 * flairNLPGH-2632: Fixing bug where embeddings got added twice on multiple training runs * flairNLPGH-2632: Enabling and fixing tests for param selection * flairNLPGH-2632: Fixing flake, mypy and isort issues * Dropout for all * fix first_last * Fix printouts for SequenceTagger * 🐛 Fix .pre-commit-config.yaml While trying to set up pre-commit, I got an indentation error. Moreover, pycqa/isort does not have a stable rev. I set it to the most recent release tag. * feat: ✨ initial implementation of JsonlCorpora and Datasets * flairNLPGH-2654: Fixed printing and logging inconsistencies. * Adding TransformerDocumentEmbeddings support to TextClassifierParamSelector and applying PR suggestions * Fixing flake tests * Using a small transformer in tests to reduce the CI agent memory usage * Fix find_learning_rate * Updating korean docs * removing warining from step() * fix: patch the missing `document_delmiter` for `lm.__get_state__()` * updated broken link * flairNLPGH-2654: Added review comments made by @Weyaaron * flairNLPGH-2654: Fix breaking gzip import * Making fune_tune a normal (non-tunable) parameter and defaulting it to True * refactor: pin pytest in pipfile * refactor: ♻️ make label_type configurable for Jsonl corpora * fix: pin isort correctly to major release 5 * refactor: pin isort in pipfile to major release 5 * Fix relation extractor * datasets: add support for HIPE 2022 * datasets: register NER_HIPE_2022 * tests: add extensive test cases for all sub-datasets for HIPE 2022 * Set default dropouts to 0 for equality to previous approaches * datasets: fix flake8 errors for HIPE 2022 integration * Update flair/models/language_model.py Co-authored-by: Tadej Magajna <tmagajna@gmail.com> * Formatting * datasets: add support for v2 of HIPE-2022 dataset * tests: update cases for v2 of HIPE-2022 dataset * tests: minor flake fix for datasets * tests: adjust latest HIPE v2.0 data changes for SONAR and NewsEye dataset * datasets: switch to main as default branch name for HIPE-2022 data repo * datasets: introduce some bug fixes for HIPE-2022 (tab as delimiter, ignore empty tokens) * test: include label checking tests for HIPE-2022 * datasets: beautify emtpy token fix for HIPE-2022 dataset reader * tests: fix mypy error (hopefully) * datasets: fix mypy error (hopefully) * flairNLPGH-2689: bump version numbers * different way to exclude labels * remove comment * Change printouts for all DataPoints and Labels * Black formatting * Update printouts * Update printouts to round confidence scores * Add Arabic NER models back in * Update readmes for new label logic and printouts * Make DataPoint hashable and add test * Do not add O tags * Remap relation labels * minor formatting * Changed the documentation on OneHotEmbeddings to reflect changes in the master version: OneHotEmbeddings.from_corpus() instead of OneHotEmbeddings(). * Nicer printouts for make_label_dictionary * Update documentation * Black formatting * small fixes * Global arrow symbol * Global arrow symbol * Update relation model * Fix unit test * Fix unit tests * datasets import * Update documentation * Update TUTORIAL_7_TRAINING_A_MODEL.md * datasets: add possibility to use custom preprocessing function for HIPE-2022 * datasets: fix mypy error for HIPE-2022 preprocessing function * datasets: revert self from HIPE-2022 preprocessing fn * datasets: fix preprocessing function handling in HIPE-2022 * Minor fixes for tutorials * Fix the SciSpacyTokenizer.tokenize() bug. Makes sure the words are added to the correct list variable and that strings, not SpaCy Token objects, are returned. * Fixing Hunflair docs that depended on SciSpacyTokenizer * flairNLPGH-2713: make transformer offset calculation more robust * flairNLPGH-2717: add option to ignore labels to ColumnCorpus * flairNLPGH-2717: formatting * flairNLPGH-2689: bump version numbers to 0.11.1 * flairNLPGH-2720: handle consecutive whitespaces * add exclude labels parameter to trainer.train and minor change in AIDA corpus * minor formatting * minor formating * Remove unnecessary more-itertools pin The dependency and the pin were added in https://github.com/flairNLP/flair/pull/2312/files. more-itertools is a pretty stable library. * fix wrong initialisations of label (where data_type was missing) and reintroduce working version of "return_probabilities_for_all_classes" for sequence tagger * datasets: add support for version 2.1 of HIPE-2022 * added missing property decorator * add encoding=utf-8 to file handles in NER_HIPE_2022 corpus * minor formatting * flairNLPGH-2728: add option to force token-level predictions * Move files to fix unit tests * Adapt dataset name depending on whether use_ids_and_check_existence is set * Fix unit tests for GERMEVAL dataset rename * Ignore deviation in signature in mypy * Black formattin * Extend span detection logic * flairNLPGH-2722: make span detection more robust * Add missing data * cache models used in testing to speed up tests * create cache folder if it doesn't exist * set cache to local folder * don't create redundant cache prefix * fix mypy error * dummy commit to see how fast tests run with caching * don't force creation of cache folder (as it should be created whenever needed anyways) * flairNLPGH-2754: bump version numbers * Update gdown requirement Advance gdown to latest release. * flairNLPGH-2763: remove legacy TransformerXLEmbeddings class * flairNLPGH-2765: Test with Python 3.7 * fix unit tests * flairNLPGH-2770: bump version numbers Co-authored-by: Tadej Magajna <tmagajna@gmail.com> Co-authored-by: Alan Akbik <alan.akbik@gmail.com> Co-authored-by: AnotherStranger <AnotherStranger@users.noreply.github.com> Co-authored-by: Xabier Lahuerta Vázquez <xlahuerta@protonmail.com> Co-authored-by: Mike Tian-Jian Jiang <tmjiang@gmail.com> Co-authored-by: Rishivant Singh <rishivant.singh@knoldus.com> Co-authored-by: Stefan Schweter <stefan@schweter.it> Co-authored-by: Marcel <marcelmilch@gmx.de> Co-authored-by: j <9658618+stw2@users.noreply.github.com> Co-authored-by: Benedikt Fuchs <e1526472@student.tuwien.ac.at> Co-authored-by: mauryaland <amaury@fouret.org> Co-authored-by: Shantanu <12621235+hauntsaninja@users.noreply.github.com> Co-authored-by: susannaruecker <susanna.ruecker@hu-berlin.de> Co-authored-by: upgradvisor-bot <92053865+upgradvisor-bot@users.noreply.github.com>
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Hi, I am using the following line of code to create contextualized embeddings from a biomedical roberta model.
However, when executing the code, I get the following error:
This does not occur using other hugging face library models, what could be the error in the model? Here is the link to the repository:
https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-clinical-es
Thanks
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