adapters
trankit
| adapters | trankit | |
|---|---|---|
| 4 | 1 | |
| 2,398 | 707 | |
| 1.9% | - | |
| 8.6 | 5.7 | |
| 4 days ago | 19 days ago | |
| Jupyter Notebook | Python | |
| Apache License 2.0 | Apache License 2.0 |
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adapters
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[D] NLP question: does fine-tuning train input embedding?
Usually in computer vision resnets, people finetune only the last layers, but in NLP you tune the entire model. There are also plenty of instances where people try to not do this, such as in adapters, however.
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[P] AdapterHub v2: Lightweight Transfer Learning with Transformers and Adapters
GitHub: https://github.com/Adapter-Hub/adapter-transformers
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Our new state-of-the-art multilingual NLP Toolkit - Trankit has been released
Thanks for the question. The main libraries that Trankit's using are pytorch and adapter-transformers. For the GPU requirement, we have tested our toolkit on different scenarios and found that a single GPU with 4GB of memory would be enough for a comfortable use.
trankit
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Trankit v1.0.0 - An open-source Transformer-based Multilingual NLP Toolkit for 56 languages is out.
Trankit is written in Python and can be easily installed via pip. Our code and pretrained models are publicly available at: https://github.com/nlp-uoregon/trankit
What are some alternatives?
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flair - A very simple framework for state-of-the-art Natural Language Processing (NLP)