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: 411 Bytes
6bbbc6f 0ebdb4f 6bbbc6f 0ebdb4f 6bbbc6f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"location": "/workspace/scratch/tokenizer-hf-focused-release",
"revision": null,
"status": "passed",
"default_and_variants_checked": 20,
"probes_per_variant": 6,
"checks": [
"artifact_hashes",
"special_ids",
"vocabulary_size",
"token_id_equivalence",
"exact_roundtrips",
"no_automatic_boundaries"
],
"transformers_version": "4.57.6",
"tokenizers_version": "0.22.2"
}
|