Instructions to use RedHatAI/oBERT-3-downstream-pruned-block4-80-QAT-squadv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RedHatAI/oBERT-3-downstream-pruned-block4-80-QAT-squadv1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RedHatAI/oBERT-3-downstream-pruned-block4-80-QAT-squadv1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5050a96d06a152cc9db3925526364c36c4a0bde3504bc894e066043d8be6ae5
- Size of remote file:
- 392 Bytes
- SHA256:
- 462289b0659df0461a5258f6d095dc618ed2244eabe171c42a2da3e299902775
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.