Instructions to use WindstormLabs/translate-en-af with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-en-af 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-en-af")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-en-af", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9307c32149cf402fb8e3c79bb28d624a8f42b9022daed247def84b3d87fef75
- Size of remote file:
- 75.6 MB
- SHA256:
- f5f215c7a6bdba8c67ddc844fe1fb9207f068a44868c73f5f4edb5a9c9531a31
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.