Instructions to use ZZ99/deberta-v3-large-tapt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZZ99/deberta-v3-large-tapt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ZZ99/deberta-v3-large-tapt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ZZ99/deberta-v3-large-tapt") model = AutoModelForMaskedLM.from_pretrained("ZZ99/deberta-v3-large-tapt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from ZZ99/deberta-v3-large-tapt: direct link, hf CLI and curl.
- Browser
- Download file 399 Bytes
-
https://huggingface.co/ZZ99/deberta-v3-large-tapt/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://ZZ99/deberta-v3-large-tapt/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/ZZ99/deberta-v3-large-tapt/resolve/main/tokenizer_config.json
399 Bytes
| {"do_lower_case": false, "bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "split_by_punct": false, "vocab_type": "spm", "special_tokens_map_file": null, "name_or_path": "/root/autodl-tmp/nbme/tmp/test-mlm/deberta-v3-large-tapt", "sp_model_kwargs": {}, "tokenizer_class": "DebertaV2Tokenizer"} |