Instructions to use WindstormLabs/translate-lt-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-lt-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-lt-sv")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-lt-sv", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2424eefb608c0c3c9b2390682bc05c19ed9f5e62079053b6531d13487bfa13cc
- Size of remote file:
- 829 kB
- SHA256:
- d2b47b41680ced5d4144d1f1cc37edfbe28e38e01fe5e6e69e9b834e919a6a65
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.