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👱 Arc2Face: A Foundation Model of Human Faces
TL; DR: a large dataset of high-resolution facial images, as well as a face generation model trained on its basis, which:
▪capable of creating photorealistic generations in a few seconds
▪provides complete similarity of generations to the target image compared to other existing models
▪built on the basis of Stable Diffusion and can be configured for any generation options, for example, different poses / facial expressions, etc.
▪ Github: https://github.com/foivospar/Arc2Face
▪ Project: https://arc2face.github.io
▪ Demo: https://huggingface.co/spaces/FoivosPar/Arc2Face
▪ Paper: https://arxiv.org/abs/2403.11641
✅ Telegram: https://news.1rj.ru/str/DataScienceT
TL; DR: a large dataset of high-resolution facial images, as well as a face generation model trained on its basis, which:
▪capable of creating photorealistic generations in a few seconds
▪provides complete similarity of generations to the target image compared to other existing models
▪built on the basis of Stable Diffusion and can be configured for any generation options, for example, different poses / facial expressions, etc.
▪ Github: https://github.com/foivospar/Arc2Face
▪ Project: https://arc2face.github.io
▪ Demo: https://huggingface.co/spaces/FoivosPar/Arc2Face
▪ Paper: https://arxiv.org/abs/2403.11641
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🏢University: Chung-Ang University, Republic of Korea
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⚡️ LLocalSearch: completely locally running meta search engine using LLM Agents
It is a completely local metasearch engine using LLM agents.
The user can ask a question, and the system will use a chain of AI agents to find the answer. The user can see the progress of the work and the final answer. No OpenAI or Google API keys are required.
▪ Github
✅ Telegram: https://news.1rj.ru/str/DataScienceT
It is a completely local metasearch engine using LLM agents.
The user can ask a question, and the system will use a chain of AI agents to find the answer. The user can see the progress of the work and the final answer. No OpenAI or Google API keys are required.
▪ Github
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With this library, you can generate realistic financial data sets in 5 lines of code, based on SEC reports such as 10-Ks, 10-Qs and other financial reports.
Such datasets are useful for:
• LLM assessments
• LLM fine tuning
• testing of financial instruments
• and much more
The project is completely open source.
pip financial-datasets.▪ GitHub : https://github.com/virattt/financial-datasets
▪ Example with code: https://colab.research.google.com/gist/virattt/f9b5a0ae82cc0caab57df5dedc2927c9/intro-financial-datasets.ipynb#scrollTo=K-b_1BPtJsS1
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▪ Github: https://github.com/AssafSinger94/dino-tracker
▪ Project: https://dino-tracker.github.io/
▪ Paper: https://arxiv.org/abs/2403.14548
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CameraCtrl is a model that provides precise control of the camera position, which allows you to accurately control camera angles and movements when generating a view.
▪ Github: https://github.com/hehao13/CameraCtrl
▪ Paper: http://arxiv.org/abs/2404.02101
▪ Project: https://hehao13.github.io/projects-CameraCtrl/
▪ Weights: https://huggingface.co/hehao13/CameraCtrl/tree/main
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