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:
- 1e5f3aaa4769015248c8e3676c4865ed83cd8aeea12f6c3f76a9bf17aefdb224
- Size of remote file:
- 19 MB
- SHA256:
- d88bc4a89200022c32695296bca7bf61dc9fc8ffc6cced381c6fdc414f1d671b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.