Text Classification
Adapters
Safetensors
Chinese
bert
Multi-label Text Classification
Eval Results (legacy)
Instructions to use scfengv/TVL_GeneralLayerClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use scfengv/TVL_GeneralLayerClassifier with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("scfengv/TVL_GeneralLayerClassifier", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from scfengv/TVL_GeneralLayerClassifier: direct link, hf CLI and curl.
- Browser
- Download file 367 Bytes
-
https://huggingface.co/scfengv/TVL_GeneralLayerClassifier/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://scfengv/TVL_GeneralLayerClassifier/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/scfengv/TVL_GeneralLayerClassifier/resolve/main/tokenizer_config.json
367 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": false, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 512, | |
| "never_split": null, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |