Instructions to use WindstormLabs/translate-sv-mfe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-sv-mfe 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-mfe")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-sv-mfe", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 235aeb246fcbe19f56f060db57da5d76d44aad963dd6a14ee4baf7f54910eb6e
- Size of remote file:
- 660 kB
- SHA256:
- 58c86f608336fc3ed142141d07ffb867b6de7d2d15110f1d97d46d828789c3ad
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.