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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@@ -81,8 +81,8 @@ These are all the available formats. Weight file is named `{name}_{quant}.gguf`
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| model-xl-4_0 | xl | 4_0 | 3B | 1.6 GB |
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| - | [xxl](https://huggingface.co/grammarly/coedit-xxl) | None | 11B | 44.5 GB |
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| model-xxl | xxl | 6k | 11B | 9.14 GB |
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| model-xxl-4k | xxl | 4k | 11B |
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| model-xxl-4_0 | xxl | 4_0 | 11B |
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## Model generation
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| model-xl-4_0 | xl | 4_0 | 3B | 1.6 GB |
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| - | [xxl](https://huggingface.co/grammarly/coedit-xxl) | None | 11B | 44.5 GB |
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| model-xxl | xxl | 6k | 11B | 9.14 GB |
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| model-xxl-4k | xxl | 4k | 11B | 6.27 GB |
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| model-xxl-4_0 | xxl | 4_0 | 11B | 6.27 GB |
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## Model generation
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