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Mohamed Sadek Saadi

yohoji
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reacted to jasoncorkill's post with 🚀 1 day ago
Has OpenGVLab Lumina Outperformed OpenAI’s Model? We’ve just released the results from a large-scale human evaluation (400k annotations) of OpenGVLab’s newest text-to-image model, Lumina. Surprisingly, Lumina outperforms OpenAI’s DALL-E 3 in terms of alignment, although it ranks #6 in our overall human preference benchmark. To support further development in text-to-image models, we’re making our entire human-annotated dataset publicly available. If you’re working on model improvements and need high-quality data, feel free to explore. We welcome your feedback and look forward to any insights you might share! https://huggingface.co./datasets/Rapidata/OpenGVLab_Lumina_t2i_human_preference
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Rapidata/OpenGVLab_Lumina_t2i_human_preference
reacted to jasoncorkill's post with 🚀 8 days ago
This dataset was collected in roughly 4 hours using the Rapidata Python API, showcasing how quickly large-scale annotations can be performed with the right tooling! All that at less than the cost of a single hour of a typical ML engineer in Zurich! The new dataset of ~22,000 human annotations evaluating AI-generated videos based on different dimensions, such as Prompt-Video Alignment, Word for Word Prompt Alignment, Style, Speed of Time flow and Quality of Physics. https://huggingface.co./datasets/Rapidata/text-2-video-Rich-Human-Feedback
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