Instructions to use WindstormLabs/translate-ja-vi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-ja-vi 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-vi")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-ja-vi", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d590f39b7ea5ca89f7d51a09e1bcbf885656060453bc7902feada2b75abb9869
- Size of remote file:
- 763 kB
- SHA256:
- 391b0ec9aac4540171656ab73d5c86e9b60b1e74cbd449f9a3bca735eae02cbb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.