Instructions to use sumanthbhargava/bart-base-encoding-correction-1k-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumanthbhargava/bart-base-encoding-correction-1k-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sumanthbhargava/bart-base-encoding-correction-1k-v2") model = AutoModelForSeq2SeqLM.from_pretrained("sumanthbhargava/bart-base-encoding-correction-1k-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 416 Bytes
5a6c38c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"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>"
}
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