Creating a dataset to fine-tune Mamba 🐍

The PIQA dataset introduces the task of physical commonsense reasoning and a corresponding benchmark dataset Physical Interaction: Question Answering or PIQA.

Models trained to recognize emotions in faces

Dataset of black and white 44x44 pixel images to detect emotion

37 category pet dataset with roughly 200 images for each class. The images have a large variations in scale, pose and lighting. All images have an associated ground truth annotation of breed, head ROI, and pixel level trimap segmentation.

This is a dataset of practical LLM instructions across tasks that tasks we actually use these models for such as coding, reasoning, math, writing, etc.

This dataset provides access to ImageNet (ILSVRC) 2012 which is the most commonly used subset of ImageNet. This dataset spans 1000 object classes and contains 1 million+ training images, 50,000 validation images and 100,000 test images.

An image classification dataset containing 3670 images of flowers across 5 classes: daisy, dandelion, roses, sunflowers, tulips. The images are of nonstandard sizes and aspect ratios, ranging from 500 x 442 px to 143 x 240 px.