Keras Hub 0.22.1 is out 
Highlights of this release
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Gemma 3 270M: Released Gemma 3 270M parameter model and instruction tuned, 18-layer, text-only model designed for hyper-efficient AI, particularly for task-specific fine-tuning.
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Qwen3: A powerful, large-scale multilingual language model, excelling in various natural language processing tasks, from text generation to complex reasoning.
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DeiT: Data-efficient Image Transformers (DeiT), specifically designed to train Vision Transformers effectively with less data, making high-performance visual models more accessible.
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HGNetV2: An advanced version of the Hybrid-Grouped Network, known for its efficient architecture in computer vision tasks, particularly optimized for performance on diverse hardware.
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DINOV2: A state-of-the-art Self-Supervised Vision Transformer, enabling the learning of robust visual representations without relying on explicit labels, ideal for foundation models.
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ESM & ESM2: Evolutionary Scale Modeling (ESM & ESM2), powerful protein language models used for understanding protein sequences and structures, with ESM2 offering improved capabilities for bioinformatics research.
Read more about the release in release note: Releases · keras-team/keras-hub · GitHub