Instructions to use mradermacher/GLM-4.5-Base-i1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/GLM-4.5-Base-i1-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/GLM-4.5-Base-i1-GGUF", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd932a618676614953a52efc92a1b97d1acf7f037efb87bf64acada0c87e1a81
- Size of remote file:
- 49.4 GB
- SHA256:
- 1f69cd1fc8fdfbbbf97946f76deda1748a10a748ffabcb92a0016c37bb26d32a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.