Instructions to use EngineeringSoftware/EditsTranlation-java2cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EngineeringSoftware/EditsTranlation-java2cs with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("EngineeringSoftware/EditsTranlation-java2cs") model = AutoModelForMultimodalLM.from_pretrained("EngineeringSoftware/EditsTranlation-java2cs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 26831987d43e6c51167822b185e4031c3051be4474dac166bfbbe03f52a454f6
- Size of remote file:
- 892 MB
- SHA256:
- ba7b63dbe73238a5515eaaf61568b37cede80b93f08b75cd30f1a016d024255b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.