Instructions to use jbochi/candle-coedit-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jbochi/candle-coedit-quantized with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jbochi/candle-coedit-quantized") model = AutoModelForSeq2SeqLM.from_pretrained("jbochi/candle-coedit-quantized") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5820392354048b66dc45e6d9c0b2e2d6656839a9f4d0d1036c4821c2f735dc7
- Size of remote file:
- 643 MB
- SHA256:
- b593ff2221b7b219e9a43cad923cb8d86386982ecb794ee9f1a8b5390b942ed2
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