Instructions to use nbbquoc/mamba_text_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbbquoc/mamba_text_classification with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nbbquoc/mamba_text_classification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- efe3f5bca0ed33f8590b998653ded6f4ffa350e710119493ed6d37cc82d5d124
- Size of remote file:
- 5.11 kB
- SHA256:
- 4e1d8ad0e57fc2ccb8878cfc888dcbb437c50f01a4341206c7cdb546894b4e83
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.