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:
- f54fe4a1a1db9cac6ef3c3dbe8c5805f0b640a956ec936e8b06f2142986da1ce
- Size of remote file:
- 2.34 GB
- SHA256:
- d6958013a27ef55d0c5c6ce5562e481847c4711808ec6af7fb8e6a4d503a1e52
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