Instructions to use kanishka/GlossBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kanishka/GlossBERT with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kanishka/GlossBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from kanishka/GlossBERT: direct link, hf CLI and curl.
- Browser
- Download file 333 Bytes
-
https://huggingface.co/kanishka/GlossBERT/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://kanishka/GlossBERT/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/kanishka/GlossBERT/resolve/main/tokenizer_config.json
333 Bytes
| {"do_lower_case": true, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "bert-base-uncased"} |