Instructions to use WindstormLabs/translate-sv-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-sv-fr 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-sv-fr")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-sv-fr", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 55a79e61e2b8506bfdef1a7e8e610f77746eb05cd2349b872c48d306084d7b18
- Size of remote file:
- 826 kB
- SHA256:
- 6ffb1c44197eb5983cf7afa0b928113b81851c3d36125c8e45de89e58a215392
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.