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:
- 61dd4c4d11160c4872c8d387e03919eff8f6ada732cf1667f0d4f8ff5775a936
- Size of remote file:
- 19 MB
- SHA256:
- faa5fd315cf320916b53b7041d32b1e2b5deda9f592399fcedb1acd76d84a9ca
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.