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_quantized.onnx from Maimonator/coedit-large-onnx: direct link, hf CLI and curl.
- Browser
- Download file 478 MB
-
https://huggingface.co/Maimonator/coedit-large-onnx/resolve/main/onnx/decoder_model_quantized.onnx
- Command line
-
hf download hf://Maimonator/coedit-large-onnx/onnx/decoder_model_quantized.onnx
-
curl -L -o decoder_model_quantized.onnx https://huggingface.co/Maimonator/coedit-large-onnx/resolve/main/onnx/decoder_model_quantized.onnx
478 MB
- Xet hash:
- 69caf51611ca31032afb889b76b6985d82331dcd60c31e402b30dbbaae435a0d
- Size of remote file:
- 478 MB
- SHA256:
- b561c2e9188aa542ead0bbae5318d5b0b03c24518f1242ed582e83d43625ef42
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