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
Download variants/structured-code-v1-32768/config.json from jfrick/scholarly-code-tokenizer: direct link, hf CLI and curl.
- Browser
- Download file 553 Bytes
-
https://huggingface.co/jfrick/scholarly-code-tokenizer/resolve/main/variants/structured-code-v1-32768/config.json
- Command line
-
hf download hf://jfrick/scholarly-code-tokenizer/variants/structured-code-v1-32768/config.json
-
curl -L -o config.json https://huggingface.co/jfrick/scholarly-code-tokenizer/resolve/main/variants/structured-code-v1-32768/config.json
553 Bytes
| { | |
| "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 | |
| } | |