Instructions to use WindstormLabs/translate-de-tl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-de-tl 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-de-tl")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-de-tl", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e9acfb2e367d0f11b9996e657d6f64bd7ae93680b02f6adf3cd3c98815e81c24
- Size of remote file:
- 857 kB
- SHA256:
- d7e76daf8d5a721ac8d155b1f0d7e0a0368f31b52eeb3639acb1e0b253598fb5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.