Instructions to use UKP-SQuARE/spanbert-base-cased-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UKP-SQuARE/spanbert-base-cased-onnx with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("UKP-SQuARE/spanbert-base-cased-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from UKP-SQuARE/spanbert-base-cased-onnx: direct link, hf CLI and curl.
- Browser
- Download file 384 Bytes
-
https://huggingface.co/UKP-SQuARE/spanbert-base-cased-onnx/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://UKP-SQuARE/spanbert-base-cased-onnx/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/UKP-SQuARE/spanbert-base-cased-onnx/resolve/main/tokenizer_config.json
384 Bytes
| { | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": true, | |
| "mask_token": "[MASK]", | |
| "name_or_path": "SpanBERT/spanbert-base-cased", | |
| "never_split": null, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "special_tokens_map_file": null, | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |