Instructions to use swapit/dev_on with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use swapit/dev_on with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("swapit/dev_on", set_active=True) - Notebooks
- Google Colab
- Kaggle
| license: wtfpl | |
| datasets: | |
| - saiyan-world/Goku-MovieGenBench | |
| - open-thoughts/OpenThoughts-114k | |
| - axxkaya/UVT-Explanatory-based-Vision-Tasks | |
| - Rapidata/sora-video-generation-physics-likert-scoring | |
| - Rapidata/sora-video-generation-time-flow | |
| language: | |
| - en | |
| metrics: | |
| - accuracy | |
| - character | |
| - code_eval | |
| base_model: | |
| - black-forest-labs/FLUX.1-dev | |
| new_version: Wan-AI/Wan2.1-T2V-14B | |
| pipeline_tag: image-to-video | |
| library_name: adapter-transformers | |
| tags: | |
| - biology | |