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Anyone can create free hosted tools for their AI agents! ๐ฅ 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
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nyuuzyou
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๐ฑ 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.
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Simple Summarization on DeepSeek-R1 from DeepSeek AI The RL stage is very important. โณ However, it is difficult to create a truly helpful AI for people solely through RL. โณ 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. โณ 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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arxiv:
2401.13601
arxiv:
2309.12792
arxiv:
2302.04023
arxiv:
2204.09934
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