Instructions to use Xenova/ClinicalBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use Xenova/ClinicalBERT with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('feature-extraction', 'Xenova/ClinicalBERT');
Download tokenizer_config.json from Xenova/ClinicalBERT: direct link, hf CLI and curl.
- Browser
- Download file 431 Bytes
-
https://huggingface.co/Xenova/ClinicalBERT/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Xenova/ClinicalBERT/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Xenova/ClinicalBERT/resolve/main/tokenizer_config.json
431 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": true, | |
| "full_tokenizer_file": null, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "never_split": null, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "DistilBertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |