Instructions to use RedHatAI/oBERT-12-downstream-pruned-block4-90-squadv1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RedHatAI/oBERT-12-downstream-pruned-block4-90-squadv1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RedHatAI/oBERT-12-downstream-pruned-block4-90-squadv1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d5b522f6d9c9c5d55bbeb99fbc6199a3659f01ad8f1f9a5b9501c4cfbaef90d
- Size of remote file:
- 590 kB
- SHA256:
- ae68c7fd21c999b58554b0e77ce6a8bc8b1dddfb48e9ebe1e24178423667b09b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.