Instructions to use WindyWord/translate-run-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyWord/translate-run-es 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-run-es")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindyWord/translate-run-es", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a1052a00bf9d91b1b32beb2b46d738dcd339d8a7baabca880a2252ed6dfacdd
- Size of remote file:
- 811 kB
- SHA256:
- 64043a25bfdb7e887c85c96c78cbf6a0c01cec5fbd96468cd9f96ee0d5d2245c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.