Instructions to use mradermacher/DeepSeek-V3-0324-Pruned-Coder-411B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/DeepSeek-V3-0324-Pruned-Coder-411B-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/DeepSeek-V3-0324-Pruned-Coder-411B-GGUF", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2daa3d514c92a693e2e59c725960e4954f4c58116db454c969f01dca6b5c3f39
- Size of remote file:
- 44 GB
- SHA256:
- 497ccff7e040e90b038dd55a43440dc19770562c353d07620b65813fdf344f14
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.