Instructions to use WindstormLabs/translate-de-ha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-de-ha 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-ha")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-de-ha", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3abbf439c9e8114371c425c7401ce33f623bcb0df2d16771f90f77e811bf46c6
- Size of remote file:
- 862 kB
- SHA256:
- 7baa5f55b6291f86cdbf25b823c3b043ac78c29f2f571e5147f0b5b5f0630121
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.