Instructions to use sumanthbhargava/bart-base-encoding-correction-10k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumanthbhargava/bart-base-encoding-correction-10k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sumanthbhargava/bart-base-encoding-correction-10k") model = AutoModelForSeq2SeqLM.from_pretrained("sumanthbhargava/bart-base-encoding-correction-10k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from sumanthbhargava/bart-base-encoding-correction-10k: direct link, hf CLI and curl.
- Browser
- Download file 416 Bytes
-
https://huggingface.co/sumanthbhargava/bart-base-encoding-correction-10k/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://sumanthbhargava/bart-base-encoding-correction-10k/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/sumanthbhargava/bart-base-encoding-correction-10k/resolve/main/tokenizer_config.json
416 Bytes
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "errors": "replace", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "RobertaTokenizer", | |
| "trim_offsets": true, | |
| "unk_token": "<unk>" | |
| } | |