Instructions to use tner/deberta-v3-large-btc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/deberta-v3-large-btc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/deberta-v3-large-btc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/deberta-v3-large-btc") model = AutoModelForTokenClassification.from_pretrained("tner/deberta-v3-large-btc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from tner/deberta-v3-large-btc: direct link, hf CLI and curl.
- Browser
- Download file 425 Bytes
-
https://huggingface.co/tner/deberta-v3-large-btc/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://tner/deberta-v3-large-btc/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/tner/deberta-v3-large-btc/resolve/main/tokenizer_config.json
425 Bytes
| { | |
| "bos_token": "[CLS]", | |
| "cls_token": "[CLS]", | |
| "do_lower_case": false, | |
| "eos_token": "[SEP]", | |
| "mask_token": "[MASK]", | |
| "name_or_path": "tner_ckpt/btc_deberta_v3_large/model_lzavco/epoch_5", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "sp_model_kwargs": {}, | |
| "special_tokens_map_file": null, | |
| "split_by_punct": false, | |
| "tokenizer_class": "DebertaV2Tokenizer", | |
| "unk_token": "[UNK]", | |
| "vocab_type": "spm" | |
| } | |