Instructions to use datasciencemmw/old-beta2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use datasciencemmw/old-beta2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="datasciencemmw/old-beta2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("datasciencemmw/old-beta2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85e9114dbb4644184b3ee5869fe9601cc139e88b6ae5b811c1d842b9594edd7a
- Size of remote file:
- 963 Bytes
- SHA256:
- dea11db03530c61ee1a7d7702c0cbbcaaf8635dca038b31e4ad87451c88887b9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.