Instructions to use ppak10/defect-classification-scibert-baseline-25-epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ppak10/defect-classification-scibert-baseline-25-epochs with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ppak10/defect-classification-scibert-baseline-25-epochs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc4836aa70fb408df943d3382cd6a3e2e3e5cc1ae0512c4c8b9d783db7223bb6
- Size of remote file:
- 13.9 kB
- SHA256:
- e40d6eff33d6d509b05da205f6f693d343ff9d74b3a26102d009cf414db7f89f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.