Instructions to use hellonlp/promcse-bert-base-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hellonlp/promcse-bert-base-zh with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, BertForCL tokenizer = AutoTokenizer.from_pretrained("hellonlp/promcse-bert-base-zh") model = BertForCL.from_pretrained("hellonlp/promcse-bert-base-zh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from hellonlp/promcse-bert-base-zh: direct link, hf CLI and curl.
- Browser
- Download file 362 Bytes
-
https://huggingface.co/hellonlp/promcse-bert-base-zh/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://hellonlp/promcse-bert-base-zh/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/hellonlp/promcse-bert-base-zh/resolve/main/tokenizer_config.json
362 Bytes
| {"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": null, "name_or_path": "/home/work/chenming6/ee/text-similarity/promcse_zh/promcse/bert_pytorch", "do_basic_tokenize": true, "never_split": null} |