Instructions to use inclusionAI/LLaDA2.0-flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inclusionAI/LLaDA2.0-flash with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("inclusionAI/LLaDA2.0-flash", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fbac74f12a1c2850ddad1edd0f3682261382d6ebd14f1076c1b6c29f6b64a302
- Size of remote file:
- 4.99 GB
- SHA256:
- 2da5c3536a4c881c63342a0e9b8b7df56903131cab2705128fccad91aefc41f2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.