Instructions to use sumanthbhargava/mt5-base-encoding-correction-1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumanthbhargava/mt5-base-encoding-correction-1k with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sumanthbhargava/mt5-base-encoding-correction-1k") model = AutoModelForSeq2SeqLM.from_pretrained("sumanthbhargava/mt5-base-encoding-correction-1k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 305 Bytes
4144fa3 ac1ef74 4144fa3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"backend": "tokenizers",
"eos_token": "</s>",
"extra_ids": 0,
"extra_special_tokens": [],
"is_local": false,
"local_files_only": false,
"model_max_length": 1000000000000000019884624838656,
"pad_token": "<pad>",
"tokenizer_class": "T5Tokenizer",
"unk_id": 2,
"unk_token": "<unk>"
}
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