Instructions to use llmware/deepseek-r1-distill-qwen-7b-onnx-qnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use llmware/deepseek-r1-distill-qwen-7b-onnx-qnn with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("llmware/deepseek-r1-distill-qwen-7b-onnx-qnn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a79bcc75e8e6b5674e23f8b61d9a1d1187e2aa746dbb9268a93aea419126e107
- Size of remote file:
- 2.16 MB
- SHA256:
- f4ed7c749425ca08a085bbb970329ad305e3b10070e931d99f4b6e614aa4c5b1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.