Instructions to use WindyWord/translate-sem-sem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-sem-sem 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-sem-sem")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-sem-sem", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51878368753fa9b99230d83b964e2f641f7369d592d1c254d2f29c59adc76b96
- Size of remote file:
- 852 kB
- SHA256:
- f7189ba46873626410ddb99b0c5a3dd4eed951b459471d057d4526d8b4fe68c9
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