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 research/source-comparisons.png from jfrick/scholarly-code-tokenizer: direct link, hf CLI and curl.
- Browser
- Download file 407 kB
-
https://huggingface.co/jfrick/scholarly-code-tokenizer/resolve/main/research/source-comparisons.png
- Command line
-
hf download hf://jfrick/scholarly-code-tokenizer/research/source-comparisons.png
-
curl -L -o source-comparisons.png https://huggingface.co/jfrick/scholarly-code-tokenizer/resolve/main/research/source-comparisons.png
407 kB

- Xet hash:
- d1a80e51ea86c2119f7dda846987b74d798df141df683ff101cf42111136a8be
- Size of remote file:
- 407 kB
- SHA256:
- 1e96d6ad85993c2c7492eac831c42a0a9f1376358a322abd989a15f197d85a98
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