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 local-verification.json from jfrick/scholarly-code-tokenizer: direct link, hf CLI and curl.
- Browser
- Download file 411 Bytes
-
https://huggingface.co/jfrick/scholarly-code-tokenizer/resolve/main/local-verification.json
- Command line
-
hf download hf://jfrick/scholarly-code-tokenizer/local-verification.json
-
curl -L -o local-verification.json https://huggingface.co/jfrick/scholarly-code-tokenizer/resolve/main/local-verification.json
411 Bytes
| { | |
| "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" | |
| } | |