v0.23.0

Summary:

New Models:

We've integrated a range of cutting-edge models, each designed to tackle specific challenges in their respective domains:

• Cell2Sentence: A single-cell, biology-aware model built on the Gemma-2 architecture, designed to interpret complex biological data.

• T5Gemma: A new encoder-decoder model, ideal for sequence-to-sequence tasks like translation and summarization.

• PARSeq: An end-to-end, ViT-based model for scene text recognition (STR), excelling at reading text in natural images.

• D-FINE: A high-performance, real-time object detection model.

• DepthAnythingV2: A monocular depth estimation (MDE) model trained on a combination of synthetic labeled data and real-world unlabeled images.

• Qwen3 Moe: The largest language model in the Qwen series, utilizing a Mixture-of-Experts (MoE) architecture for enhanced performance and efficiency.

• MobileNetV5: A state-of-the-art vision encoder specifically designed for high-efficiency AI on edge devices.

• SmolLM3: A compact yet powerful language model excelling in reasoning, long-context understanding, and multilingual capabilities.

Improvements & Enhancements

This update also includes several key improvements to enhance the platform's stability, compatibility, and flexibility:

• export_to_transformers: You can now export trainable models, tokenizers, and configurations directly into the Hugging Face Transformers format using export_to_transformers. This feature is currently available for Gemma models, with support for more architectures coming soon.
• OpenVINO Backend Support: We've integrated OpenVINO inference support, enabling optimized inference for Mistral, Gemma, and GPT-2 models.
• Bidirectional Attention Mask: Gemma models now support a bidirectional attention mask, enabling more effective fine-tuning on tasks that require understanding the full context of a sequence.
• CLIP & SD3 Model Refactor: The CLIP and Stable Diffusion 3 models have been refactored to improve numerical stability. Updated checkpoints are now available to ensure seamless and reliable performance.

What's Changed

• Register tiny Gemma presets by @sachinprasadhs in #2360
• Update fixed preset version for gemma3 by @sachinprasadhs in #2362
• Add generic export_to_transformers to the base classes by @Bond099 in #2346
• update version file in master by @sachinprasadhs in #2361
• add styleguide for GCA code reviews by @divyashreepathihalli in #2366
• Update styleguide.md by @divyashreepathihalli in #2370
• Add T5Gemma to KerasHub by @harshaljanjani in #2339
• Allow passing flexible positions to positional embedding layers by @abheesht17 in #2369
• Supports Loading Quantized Models with from_preset() by @JyotinderSingh in #2367
• PARSeq Model by @sineeli in #2089
• Add D-FINE to KerasHub by @harshaljanjani in #2318
• Fixing dtype issue by @buildwithsuhana in #2372
• quantize(...) should accept a config object by @JyotinderSingh in #2388
• [OpenVINO backend] Adding support for OpenVINO backend & support inference for Mistral & Gemma & GPT2 by @Mohamed-Ashraf273 in #2350
• minor modify by @pass-lin in #2386
• Add bidirectional attention mask for EmbeddingGemma by @abheesht17 in #2382
• Fixes by @buildwithsuhana in #2395
• Disable DINO quantisation checks by @abheesht17 in #2397
• Introduce D-FINE model presets in KerasHub by @harshaljanjani in #2376
• Introduce T5Gemma model presets in KerasHub by @harshaljanjani in #2373
• Update CLIP presets by @abheesht17 in #2400
• Fix Gemma OpenVINO tests by @abheesht17 in #2402
• Adds support for gemma_270m to checkpoint converter by @JyotinderSingh in #2380
• [internal] Reorder @pytest.mark.large decorator to fix CI by @JyotinderSingh in #2410
• Update preset map for VGG model by @sonali-kumari1 in #2411
• Update preset map for T5 model by @sonali-kumari1 in #2414
• Update preset map values for cspnet by @dhantule in #2416
• Add DepthAnythingV2. by @james77777778 in #2377
• Add Qwen3 Moe by @kanpuriyanawab in #2260
• update hf checkpoints list by @sachinprasadhs in #2381
• Patch conversion script qwen3 moe by @kanpuriyanawab in #2425
• update SD3 & 3.5 presets by @sachinprasadhs in #2417
• Add and Register the Qwen3_MoE Presets to Hub by @laxmareddyp in #2429
• Add MobileNetV5 to KerasHub by @harshaljanjani in #2399
• For sharded weights let's not delete explicitly by @amitsrivastava78 in #2431
• Update Keras min Test version to 3.9 by @sachinprasadhs in #2434
• Overrides _post_quantize to reset generate_function graph after quantization by @JyotinderSingh in #2436
• Handles incompatible quantization mode for ReversibleEmbedding by @JyotinderSingh in #2435
• extend PR stale and closure time by @sachinprasadhs in #2437
• register depth anything presets by @sachinprasadhs in #2420
• [SmolLM3] Add Backbone, CausalLM + Converter for HuggingFace Weights by @DavidLandup0 in #2327
• Register Cell2Sentence Presets by @laxmareddyp in #2442
• register parseq preset by @sachinprasadhs in #2438
• register mobilenet presets by @sachinprasadhs in #2443
• update release version by @sachinprasadhs in #2446

New Contributors

• @buildwithsuhana made their first contribution in #2372
• @Mohamed-Ashraf273 made their first contribution in #2350
• @dhantule made their first contribution in #2416
• @amitsrivastava78 made their first contribution in #2431

Full Changelog: v0.22.2...v0.23.0