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
Commit History
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Upload 4 files for base model
https://huggingface.co/jbochi/coedit-base - sha 23419e968ed460dd8fb9dfe9c48862eefe480aca Commands: ```bash cargo run --example tensor-tools --release -- quantize --quantization q4k ~/Downloads/model.safetensors --out-file model-base-q4k.gguf cargo run --example tensor-tools --release -- quantize --quantization q4_0 ~/Downloads/model.safetensors --out-file model-base-q4_0.gguf cargo run --example tensor-tools --release -- quantize --quantization q6k ~/Downloads/model.safetensors --out-file model-base.gguf ```d920a61