Instructions to use WindstormLabs/translate-tr-lt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-tr-lt 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-tr-lt")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-tr-lt", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41365f3a6ab27f9d2db398b0ea06a0cb5b3d010b85c9228870115e17133d2f31
- Size of remote file:
- 853 kB
- SHA256:
- 8da788349c6d9ceca613db0d043478626533697410d161cef9f4a8608dc60183
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.