Instructions to use ppak10/defect-classification-t5-prompt-05-epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ppak10/defect-classification-t5-prompt-05-epochs with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ppak10/defect-classification-t5-prompt-05-epochs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ppak10/defect-classification-t5-prompt-05-epochs: direct link, hf CLI and curl.
- Browser
- Download file 141 MB
-
https://huggingface.co/ppak10/defect-classification-t5-prompt-05-epochs/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ppak10/defect-classification-t5-prompt-05-epochs/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ppak10/defect-classification-t5-prompt-05-epochs/resolve/main/pytorch_model.bin
141 MB
- Xet hash:
- 7488ce6dabe6c2db34eb1ad89a0ae1b33d41553a5570b75aa723014b38b30b12
- Size of remote file:
- 141 MB
- SHA256:
- 2d77a5c7f1bdee65ec0d91958ab6deb84f39c0a179ebe52cc267d1916b098c8a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.