Instructions to use WindyWord/translate-sv-lua with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-sv-lua 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="WindyWord/translate-sv-lua")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-sv-lua", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9411f9aff93ddbdba4da145413a6c1faf95482fa451f214a1b060781c222955d
- Size of remote file:
- 823 kB
- SHA256:
- 4fbc4ecd4463de3e93a02596fc9988371ebf4f153e5bce3dedf3ecc58ffd53a0
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