Instructions to use WindyWord/translate-fi-pag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-fi-pag 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-fi-pag")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-fi-pag", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2333e256f04f039c8eee666503526e83c466f74c29e1dec17fdbec2a88aa2863
- Size of remote file:
- 77.9 MB
- SHA256:
- d79f63fd547605be899b56d8282fc5afb95ce29145ce90b389050fc18f55fece
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.