Instructions to use nlp-project-uw/quant_1b_impl_BitNet_loss_CrossEntropy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlp-project-uw/quant_1b_impl_BitNet_loss_CrossEntropy with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nlp-project-uw/quant_1b_impl_BitNet_loss_CrossEntropy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32c464807098f42c39379bf7ea66b50a2cd79860961e7b2f24a0137953b6a4a7
- Size of remote file:
- 539 MB
- SHA256:
- 079ae2fedea0e8d00b1bb3b8d057de1d544301d72ccda9a2aa5bb69bb002c751
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.