Skip to content
#

zero-shot-classification

Here are 84 public repositories matching this topic...

Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

  • Updated Nov 25, 2024
  • Jupyter Notebook

Alternate Implementation for Zero Shot Text Classification: Instead of reframing NLI/XNLI, this reframes the text backbone of CLIP models to do ZSC. Hence, can be lightweight + supports more languages without trading-off accuracy. (Super simple, a 10th-grader could totally write this but since no 10th-grader did, I did) - Prithivi Da

  • Updated Apr 5, 2022
  • Python
text-to-image-eval

Evaluate custom and HuggingFace text-to-image/zero-shot-image-classification models like CLIP, SigLIP, DFN5B, and EVA-CLIP. Metrics include Zero-shot accuracy, Linear Probe, Image retrieval, and KNN accuracy.

  • Updated Jul 29, 2024
  • Jupyter Notebook

Improve this page

Add a description, image, and links to the zero-shot-classification topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the zero-shot-classification topic, visit your repo's landing page and select "manage topics."

Learn more