Instructions to use wolfram/miquliz-120b-v2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wolfram/miquliz-120b-v2.0 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wolfram/miquliz-120b-v2.0", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36291495a80aba85297d6d988e35d82588742855c5b447719b9aa0e67686f0ac
- Size of remote file:
- 9.8 GB
- SHA256:
- 53731c85ccb29a82b42228cb00deef88b2b58b73c4d5c0964097c631786af676
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.