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Source channel @githubtrending · Post #15365 · Dec 24

#jupyter_notebook DINOv3 offers powerful self-supervised vision models from Meta AI, like ViT up to 7B parameters and ConvNeXt, pretrained on 1.7B web or satellite images. Load them easily via PyTorch Hub, Hugging Face Transformers (v4.56+), or timm (v1.0.20+), with code examples for features, depth, detection, and segmentation. You benefit by using these top-performing, dense features without fine-tuning or labels—saving time and compute for tasks like classification, object detection, and zero-shot analysis on your images. https://github.com/facebookresearch/dinov3

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Machinelearning

@ai_machinelearning_big_data · Post #8680 · 10/02/2025, 05:01 PM

✔️IBM представила Granite 4.0 — новое семейство open-weights языковых моделей от 3B до 32B параметров. Четыре новые модели: - Granite 4.0 H Small - 32B/9B активных параметров - Granite 4.0 H Tiny - 7B/1B - Granite 4.0 H Micro - 3B/3B - Granite 4.0 Micro - 3B/3B Benchmarking (Artificial Analysis Index): - Granite 4.0 H Small: 23 балла (на 8 выше Granite 3.3 8B), обходит Gemma 3 27B (22), но уступает Mistral Small 3.2 (29) и Qwen3 30B A3B (37). - Granite 4.0 Micro: 16 баллов, выше Gemma 3 4B (15) и LFM 2 2.6B (12). ⚡ Token efficiency: - Granite 4.0 Small — 5.2M токенов - Granite 4.0 Micro — 6.7M токенов Обе модели заметно эффективнее Granite 3.3 8B и большинства non-reasoning моделей <40B. Детали: - Контекст: до 128K токенов - Лицензия: Apache 2.0 - Granite 4.0 H Small доступна на Replicate по $0.06 / $0.25 за 1M input/output токенов - Все модели доступны на Hugging Face - Модель Micro (3.4B) можно запускать полностью локально. 🔗 Hugging Face: https://huggingface.co/collections/unsloth/granite-40-68ddf64b4a8717dc22a9322d 🔗Unsloth: https://docs.unsloth.ai/new/ibm-granite-4.0 @ai_machinelearning_big_data #AI#IBM#Granite4#LLM#OpenWeights