Instructions to use WindstormLabs/translate-lua-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-lua-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-lua-sv")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-lua-sv", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce824dbc0b7d7ac1e879384fb2c30656580564f95e78132c050289ec72197026
- Size of remote file:
- 77.1 MB
- SHA256:
- f4584615d95075675f8a807421da419d8bd45766a03a83fd90d5e547e5817bf1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.