datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
CoVAtt-Benchmark
CoVAtt-Benchmark
A large-scale benchmark for generated-image attribution: given an image
that was produced by some text-to-image model, decide which model
produced it, and decide whether it came from a model the system has never
seen before.
What this dataset is
This is the dataset used to train and evaluate CoVAtt
(Content-Based Verification for Attribution of AI-Generated Images,
BMVC 2026). CoVAtt is a Siamese network that takes a pair of images and
predicts… See the full description on the dataset page: https://huggingface.co/datasets/kenyag/CoVAtt-Benchmark.kenya-bee-health-qa-image-triples
Kenya Bee Health Training Data
This folder is a starter database for BeeCare Anywhere / Gemma Apiary. It is intentionally small, transparent, and license-aware: use it to prove the Q/A/image-triple pipeline, then expand it with Kenyan field data before trusting model behavior in production.
Important Model Note
google/gemma-2b is a text-to-text, decoder-only model. It cannot directly read pictures. Use these image triples with a vision-capable model path, for… See the full description on the dataset page: https://huggingface.co/datasets/yahelr1/kenya-bee-health-qa-image-triples.