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:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jbochi/candle-coedit-quantized") model = AutoModelForSeq2SeqLM.from_pretrained("jbochi/candle-coedit-quantized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
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license: apache-2.0
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datasets:
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- grammarly/coedit
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language:
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- en
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tags:
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- text-generation-inference
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- candle
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Quantized weights of [coedit](https://github.com/vipulraheja/coedit) for inference with [candle](https://github.com/huggingface/candle/tree/main/candle-examples/examples/quantized-t5).
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