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:
- 9946457cb2b0f3d3096c94b584491fac8ae3d69776cd22b56e7e5a24c3489a07
- Size of remote file:
- 2.11 MB
- SHA256:
- 24b59b42a04c6b31ff64005a6d966a1a4863ddcc4721f7aa1cf74539db17c974
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.