Instructions to use YChang1112/basis_extraction_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YChang1112/basis_extraction_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="YChang1112/basis_extraction_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("YChang1112/basis_extraction_model") model = AutoModelForTokenClassification.from_pretrained("YChang1112/basis_extraction_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from YChang1112/basis_extraction_model: direct link, hf CLI and curl.
- Browser
- Download file 589 Bytes
-
https://huggingface.co/YChang1112/basis_extraction_model/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://YChang1112/basis_extraction_model/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/YChang1112/basis_extraction_model/resolve/main/tokenizer_config.json
589 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": false, | |
| "mask_token": "[MASK]", | |
| "max_length": 256, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "never_split": null, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "[PAD]", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "sep_token": "[SEP]", | |
| "stride": 0, | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "ElectraTokenizer", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": "[UNK]" | |
| } | |