Instructions to use cyankiwi/Qwen3-Omni-30B-A3B-Thinking-AWQ-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cyankiwi/Qwen3-Omni-30B-A3B-Thinking-AWQ-8bit with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cyankiwi/Qwen3-Omni-30B-A3B-Thinking-AWQ-8bit", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 896a1052ff7b4974c1a23522b834fad3ecfffe05ceb2fb212de57955d588a306
- Size of remote file:
- 5 GB
- SHA256:
- b700d3bfc136148de4986b5229603b940a0ab451afe5a9c1c3b9e2687e390328
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.