Instructions to use leduckhai/Sentiment-Reasoning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leduckhai/Sentiment-Reasoning with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("leduckhai/Sentiment-Reasoning", dtype="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 3e956c63aafc35dc76e49032eb556c4f12ab8e0860aa4097c6739bf8051aa878
- Size of remote file:
- 931 kB
- SHA256:
- 476c55e507089a751f16b80aa820dafc9148b74954a1b80965cb97202bd96d2f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.