Instructions to use throsturx/bihmoe-poc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use throsturx/bihmoe-poc with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("throsturx/bihmoe-poc", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| cff-version: 1.2.0 | |
| title: "bihmoe-poc: Bilateral Hierarchical MoE PoC" | |
| message: "If you use this software, please cite it as below." | |
| type: software | |
| authors: | |
| - name: "ThrosturX" | |
| repository-code: "https://huggingface.co/throsturx/bihmoe-poc" | |
| license: Apache-2.0 | |
| keywords: | |
| - transformers | |
| - mixture-of-experts | |
| - modularity | |
| - generalization | |