Instructions to use mrm8488/spanbert-base-finetuned-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/spanbert-base-finetuned-squadv2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mrm8488/spanbert-base-finetuned-squadv2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f85c27114a9a46eeede0e89ef7277916d8640747d65c8a5e403c19c62d824922
- Size of remote file:
- 667 MB
- SHA256:
- 3c752d608e8943b53fc59f5525ec35c695be8a04ed07d5d5061c7b40f3cb571a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.