Instructions to use mlml-chip/sharpseed-termexists with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlml-chip/sharpseed-termexists with Transformers:
# Load model directly from transformers import CnlpModelForClassification model = CnlpModelForClassification.from_pretrained("mlml-chip/sharpseed-termexists", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 514 Bytes
26adb3a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"add_prefix_space": true,
"additional_special_tokens": [
"<e>",
"</e>",
"<a1>",
"</a1>",
"<a2>",
"</a2>",
"<cr>",
"<neg>"
],
"bos_token": "<s>",
"cls_token": "<s>",
"eos_token": "</s>",
"errors": "replace",
"mask_token": "<mask>",
"model_max_length": 512,
"name_or_path": "roberta-base",
"pad_token": "<pad>",
"sep_token": "</s>",
"special_tokens_map_file": null,
"tokenizer_class": "RobertaTokenizer",
"trim_offsets": true,
"unk_token": "<unk>"
}
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