Instructions to use Azimml/Qwen3-1.7B-trellis-3bit-webgpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Azimml/Qwen3-1.7B-trellis-3bit-webgpu with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Azimml/Qwen3-1.7B-trellis-3bit-webgpu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a14051470a77e5f229fbedba52f79b4332982486ce85f1b344fc42cc3f0c5f3
- Size of remote file:
- 19 MB
- SHA256:
- 7097a2a83e7b23b85391172c824b9eae0806f184831ae59e9bee91c87285e8f1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.