Instructions to use WindyWord/translate-war-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-war-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-war-en")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-war-en", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6c5d42e6a70c8c1ec2a11a4917d47f16307588f0932c1204c8a63a04a0dceacb
- Size of remote file:
- 306 kB
- SHA256:
- 9ae830343f5a525e6a4790cf0596750562501e389fafce560a804b3c3ba60fa0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.