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dan su

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reacted to davidberenstein1957's post with 🤗 about 11 hours ago
Anyone can create free hosted tools for their AI agents! 🔥 Agentic RAG stack part 2 - augment Augment retrieval results by reranking optimises content without increasing time too much part2: https://huggingface.co/blog/davidberenstein1957/ai-blueprint-agentic-rag-part-2-augment code: https://github.com/huggingface/ai-blueprint
reacted to nyuuzyou's post with 👍 about 11 hours ago
📱 UI Navigation Corpus - https://huggingface.co/datasets/teleren/ui-navigation-corpus A comprehensive collection of mobile and web UI elements created by a new member of the Hugging Face community @teleren. I'm glad that I was able to provide a little help together with @its5Q to get this dataset published. This dataset contains: - Screenshots and recordings of mobile (iOS/Android) and web interfaces - UI navigation annotations and metadata - Screen categorization tags and text extractions - Navigation paths and screen relationships - Version control for UI imagery Perfect for training UI navigation agents and understanding interface patterns. The dataset provides detailed annotations linking screens, sections, and navigation flows together.
reacted to chansung's post with 👍 16 days ago
Simple Summarization on DeepSeek-R1 from DeepSeek AI The RL stage is very important. ↳ However, it is difficult to create a truly helpful AI for people solely through RL. ↳ So, we applied a learning pipeline consisting of four stages: providing a good starting point, reasoning RL, SFT, and safety RL, and achieved performance comparable to o1. ↳ Simply fine-tuning other open models with the data generated by R1-Zero (distillation) resulted in performance comparable to o1-mini. Of course, this is just a brief overview and may not be of much help. All models are accessible on Hugging Face, and the paper can be read through the GitHub repository. Model: https://huggingface.co/deepseek-ai Paper: https://github.com/deepseek-ai/DeepSeek-R1
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