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/encoder_model_quantized.onnx from Maimonator/coedit-large-onnx: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/Maimonator/coedit-large-onnx/resolve/main/onnx/encoder_model_quantized.onnx
- Command line
-
hf download hf://Maimonator/coedit-large-onnx/onnx/encoder_model_quantized.onnx
-
curl -L -o encoder_model_quantized.onnx https://huggingface.co/Maimonator/coedit-large-onnx/resolve/main/onnx/encoder_model_quantized.onnx
343 MB
- Xet hash:
- d8dc95221c1c570ec7efcc4552fc681409ccf09976c6db5d6b8d3a5b540712d1
- Size of remote file:
- 343 MB
- SHA256:
- 8c1e0d877af319053266fe3d3ea71f8d6b3f7b2568d2f72ccf2cec366695dba8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.