Instructions to use WindstormLabs/translate-tr-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-tr-en 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-en")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-tr-en", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 312ebeeadebd9679a22c18f452a727ff8aa50d04076a131152b90394d0d62133
- Size of remote file:
- 840 kB
- SHA256:
- 4a6356e3ee892f2896dbf0b5cabeb51fdf16e03c70b0702cefc8b847e504241c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.