Instructions to use Maimonator/coedit-large-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maimonator/coedit-large-onnx with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Maimonator/coedit-large-onnx") model = AutoModelForSeq2SeqLM.from_pretrained("Maimonator/coedit-large-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/decoder_model.onnx from Maimonator/coedit-large-onnx: direct link, hf CLI and curl.
- Browser
- Download file 1.9 GB
-
https://huggingface.co/Maimonator/coedit-large-onnx/resolve/main/onnx/decoder_model.onnx
- Command line
-
hf download hf://Maimonator/coedit-large-onnx/onnx/decoder_model.onnx
-
curl -L -o decoder_model.onnx https://huggingface.co/Maimonator/coedit-large-onnx/resolve/main/onnx/decoder_model.onnx
1.9 GB
- Xet hash:
- 47ae907c9056eef9d19be773344e71c03812439dd57d1236f7b8bc45f8f8b27f
- Size of remote file:
- 1.9 GB
- SHA256:
- e08b1a8a8b871fb86b77919240c2f35460042bfc3fa3381af3ba7a1266e3a61f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.