Instructions to use WindyWord/translate-sv-hil with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-sv-hil 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-hil")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-sv-hil", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e762fc96b3e3bbe0a49440457c4cef9df786916c5bb8585ae112afe0f8c12a5
- Size of remote file:
- 76.5 MB
- SHA256:
- e031007462b5896aa1dc9cd6ccb1dad4ce697b8872e06ccfced5735f67fb6f1a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.