Instructions to use WindyWord/translate-sg-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-sg-en 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-sg-en")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-sg-en", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 590e4b296ef07ae24f56fe5e8f9f8de646332ef2aa59a659538d87c6db50282e
- Size of remote file:
- 68.6 MB
- SHA256:
- b1105ce5a1f6d1fb84eec8913b14dd013b1c1883d9958945810aab84797833c9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.