Instructions to use gowitheflowlab/en-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gowitheflowlab/en-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gowitheflowlab/en-de")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("gowitheflowlab/en-de", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b63211288e636057fea959f6065745bd10566020780cf604d1c82b4b59ed7f26
- Size of remote file:
- 3.38 kB
- SHA256:
- d73524e32be1b501f8a1d86c959650ea24ba3191d50f3c2bf2d46a0d012dae71
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.