en_trf_xlnetbasecased_lg-2.2.0
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Details: https://spacy.io/models/en#en_trf_xlnetbasecased_lg
File checksum:
e769e3180783457f26136638a5b664a068b7a711b0c8dd6c01187cc7d0ee9ccf
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 | 2.2.0 |
| spaCy | >=2.2.1 |
| 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