Instructions to use jfrick/scholarly-code-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jfrick/scholarly-code-tokenizer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jfrick/scholarly-code-tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 553 Bytes
0ebdb4f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"format": "huggingface-tokenizers-json",
"vocab_size": 32768,
"special_tokens": {
"<|pad|>": 0,
"<|bos|>": 1,
"<|eos|>": 2,
"<|unk|>": 3
},
"normalization": null,
"pretokenization_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
"add_prefix_space": false,
"automatic_bos_eos": false,
"padding": null,
"truncation": null,
"decode_skip_special_tokens_default_for_roundtrips": false,
"all_valid_UTF8_supported": true
}
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