Instructions to use nealcly/detection-longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nealcly/detection-longformer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nealcly/detection-longformer", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82bb7b25d87b3e60ae3ce6067c385385b8bbde60f52efd8d51fc49521f796ca3
- Size of remote file:
- 377 Bytes
- SHA256:
- e667b8a2c557b7012bfdec7dd4cbb6066cf6ec9069f0515db0c4fc8cdb162c0f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.