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:
- 675ac13e8454d5a166266e9b7418f15d5602192b051aa9aec2974f9fbab2e2e5
- Size of remote file:
- 9.66 GB
- SHA256:
- 1a627ca60440bb5d6ce9ffd6e0f56ca5ec5b326f50e391ee629857c6c7eac630
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.