Instructions to use altndrr/cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use altndrr/cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="altndrr/cased", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("altndrr/cased", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba551177d440694eaef858e8b7d79bfa375b692382e07ac161f61921e25d2880
- Size of remote file:
- 1.71 GB
- SHA256:
- 91c5a2012ab49580ef33645ef578ab2eab491ace7ed63e856f9ef340f73e0e9e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.