Instructions to use tlkh/code-byt5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tlkh/code-byt5-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tlkh/code-byt5-large") model = AutoModelForSeq2SeqLM.from_pretrained("tlkh/code-byt5-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tlkh/code-byt5-large: direct link, hf CLI and curl.
- Browser
- Download file 4.91 GB
-
https://huggingface.co/tlkh/code-byt5-large/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://tlkh/code-byt5-large@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tlkh/code-byt5-large/resolve/refs%2Fpr%2F1/pytorch_model.bin
4.91 GB
- Xet hash:
- 7378d2660243af2d044a98453ddf86ba069fc927f9211fa51fea7d71ad556193
- Size of remote file:
- 4.91 GB
- SHA256:
- f1cb49f808f1e7f3cd17e83ca2c3e61b08e084b40a565463d7f56d10162098da
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