Instructions to use WindyWord/translate-sv-mh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-sv-mh 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="WindyWord/translate-sv-mh")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-sv-mh", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e513d1bba0e4f8df678385aeb2efb34f9608b3940111808c2a5428ea385b59b
- Size of remote file:
- 852 kB
- SHA256:
- c5893796b4adfb4936c58c659920234f19275a8ccd4142f06e50e40b92df5831
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.