Instructions to use WindstormLabs/translate-kg-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-kg-sv with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="WindstormLabs/translate-kg-sv")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-kg-sv", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9621c14681dc907ab6e32031b9f55846edc8e52a27a2b22fb1c922cb7b23b587
- Size of remote file:
- 604 kB
- SHA256:
- 566581530a4738603f5ec070f06892132c8f5d695d5e1d3aa2d81d2c5b5dca3f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.