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* Add self-training code for text-classification * Add self-training code for text-classification * Add self-training code for text-classification * Add self-training code for text-classification * Add self-training code for text-classification * Delete strata |
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| .. | ||
| adversarial | ||
| bert-loses-patience | ||
| bertabs | ||
| bertology | ||
| codeparrot | ||
| decision_transformer | ||
| deebert | ||
| distillation | ||
| fsner | ||
| jax-projects | ||
| longform-qa | ||
| luke | ||
| lxmert | ||
| mlm_wwm | ||
| mm-imdb | ||
| movement-pruning | ||
| onnx/summarization | ||
| performer | ||
| pplm | ||
| quantization-qdqbert | ||
| rag | ||
| rag-end2end-retriever | ||
| robust-speech-event | ||
| self-training-text-classification | ||
| seq2seq-distillation | ||
| tapex | ||
| visual_bert | ||
| wav2vec2 | ||
| xtreme-s | ||
| zero-shot-distillation | ||
| README.md | ||
Research projects
This folder contains various research projects using 🤗 Transformers. They are not maintained and require a specific version of 🤗 Transformers that is indicated in the requirements file of each folder. Updating them to the most recent version of the library will require some work.
To use any of them, just run the command
pip install -r requirements.txt
inside the folder of your choice.
If you need help with any of those, contact the author(s), indicated at the top of the README of each folder.