Instructions to use WindyWord/translate-fi-mfe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-fi-mfe 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-mfe")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-fi-mfe", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec0075fb0b44bcf303ffcf66cd3c4ceb27bbba3bbb7cd8f5a270fc2104161921
- Size of remote file:
- 73.9 MB
- SHA256:
- 26223bf7f297b60df725cb727f339fefd6cbbfd3927d5d74afdbf5529b8cc038
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.