Token Classification
Transformers
PyTorch
Chinese
roberta
chinese
classical chinese
literary chinese
ancient chinese
bert
punctuation marker
Instructions to use ethanyt/guwen-punc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethanyt/guwen-punc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ethanyt/guwen-punc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ethanyt/guwen-punc") model = AutoModelForTokenClassification.from_pretrained("ethanyt/guwen-punc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from ethanyt/guwen-punc: direct link, hf CLI and curl.
- Browser
- Download file 379 Bytes
-
https://huggingface.co/ethanyt/guwen-punc/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://ethanyt/guwen-punc/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/ethanyt/guwen-punc/resolve/main/tokenizer_config.json
379 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, "use_fast": true, "special_tokens_map_file": "models/guwenbert-base-fs/special_tokens_map.json", "name_or_path": "models/guwenbert-base-fs", "do_basic_tokenize": true, "never_split": null} |