Details: https://spacy.io/models/en#en_trf_xlnetbasecased_lg
File checksum:
7fa5c191ff32e1479b21f6ff79f95fe1eb6513c89ccf727b1e10c16175cb3850
Provides weights and configuration for the pretrained transformer model xlnet-base-cased, published by CMU and Google Brain. The package uses HuggingFace's transformers implementation of the model. Pretrained transformer models assign detailed contextual word representations, using knowledge drawn from a large corpus of unlabelled text. You can use the contextual word representations as features in a variety of pipeline components that can be trained on your own data.
| Feature | Description |
|---|---|
| Name | en_trf_xlnetbasecased_lg
|
| Version | 2.3.0
|
| spaCy | >=2.3.0,<2.4.0
|
| Model size | 413 MB |
| Pipeline | sentencizer, trf_wordpiecer, trf_tok2vec
|
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | xlnet-base-cased (CMU & Google Brain) |
| License | MIT
|
| Author | CMU & Google Brain (repackaged by Explosion) |
Requires the spacy-transformers package to be installed. A CUDA-compatible GPU is advised for reasonable performance.
Installation
pip install spacy
python -m spacy download en_trf_xlnetbasecased_lg