Instructions to use WindstormLabs/translate-ja-ms with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-ja-ms 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-ja-ms")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-ja-ms", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b22117e1481acdd0fa79c135487d4727c12ca7e00a053525f33a258f970479e5
- Size of remote file:
- 79.4 MB
- SHA256:
- 3df3d0b72ac391fd24fdef3b9c7693440b2a4aa8f30b9075aeb62af44d24bc4f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.