Instructions to use YCZhou/R2ANKER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YCZhou/R2ANKER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YCZhou/R2ANKER")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YCZhou/R2ANKER") model = AutoModelForSequenceClassification.from_pretrained("YCZhou/R2ANKER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from YCZhou/R2ANKER: direct link, hf CLI and curl.
- Browser
- Download file 377 Bytes
-
https://huggingface.co/YCZhou/R2ANKER/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://YCZhou/R2ANKER/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/YCZhou/R2ANKER/resolve/main/tokenizer_config.json
377 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, "full_tokenizer_file": null, "name_or_path": "nghuyong/ernie-2.0-en", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"} |