Data Science | Machine Learning with Python for Researchers
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โญ๏ธ DBRX, a groundbreaking open-source Large Language Model (LLM) with a staggering 132 billion parameters.

Databricks has just introduced DBRX, a new open source large language (LM) model with a staggering 132 billion parameters.

The model outperforms all open models on most benchmarks.

Here's what you need to know ๐Ÿ‘‡

โ€ข DBRX is a new free artificial intelligence model with 132 billion parameters.
โ€ขCan process up to 32,000 tokens simultaneously.
โ€ขTrained on 12 trillion tokens.
โ€ขFollow instructions exactly.
โ€ขOpen source on GitHub.
โ€ขIntegrated with HuggingFace.
โ€ขOptimized for NVIDIA systems.
โ€ขAdvanced configuration with Docker support.

๐ŸŸ  Github: https://github.com/databricks/dbrx

๐ŸŸ  HF: https://huggingface.co/databricks/dbrx-base

๐ŸŸ  Demo: https://huggingface.co/spaces/databricks/dbrx-instruct

๐ŸŸ  Docs: https://docs.databricks.com/en/machine-learning/foundation-models/index.html

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๐ŸŸ  DesignEdit: Multi-Layered Latent Decomposition and Fusion for Unified & Accurate Image Editing

Microsoft presents DesignEd it!

This is an image editing method that allows you to remove objects, swap objects, move them, resize them, add and flip multiple objects, make panoramas and scale images, remove objects from images.

๐ŸŸ  Github: https://github.com/design-edit/DesignEdit.git

๐ŸŸ  Paper: https://arxiv.org/abs/2403.14487

๐ŸŸ  Project: https://design-edit.github.io/

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๐Ÿ”ฅUnbounded 3D City Generation๐Ÿ”ฅ

๐Ÿ™๏ธ CityDreamer ๐Ÿ™๏ธ compositional generative model for creating full-fledged 3D cities.

โ–ช Project : https://infinitescript.com/project/city-dreamer/
โ–ช Code : https://github.com/hzxie/CityDreamer
โ–ช Demo : https://huggingface.co/spaces/hzxie/

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SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations

๐Ÿ–ฅ Github: https://github.com/divelab/AIRS

๐Ÿ“• Paper: https://arxiv.org/abs/2403.19507v1

๐Ÿ”ฅProject: www.air4.science/
Resources

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๐Ÿ“ƒ Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A Survey

๐Ÿ—“ Publish year: 2024

๐Ÿ“ฑ Authors: Qizhi Pei, Lijun Wu, Kaiyuan Gao, Jinhua Zhu, ...
๐Ÿ  University: Renmin University of China, University of Science and Technology of China, Microsoft Research

๐Ÿ“Ž Study the paper
๐Ÿ“ฆ Related sources and contents

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๐Ÿ“‘ Ten simple rules for designing graphical abstracts

๐Ÿ“• Journal: Plos Computational Biology (I.F.=4.3)
๐Ÿ—“ Publish year: 2024

๐Ÿ“ฑAuthors: Helena Klara Jambor ,Martin Bornhรคuser
๐Ÿก University: Universitรคtsklinikum Carl Gustav Carus an der Technischen Universitรคt Dresden, Germany

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๐Ÿ‘ฑ 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:

โ–ชcapable of creating photorealistic generations in a few seconds
โ–ชprovides complete similarity of generations to the target image compared to other existing models
โ–ชbuilt on the basis of Stable Diffusion and can be configured for any generation options, for example, different poses / facial expressions, etc.

โ–ช Github: https://github.com/foivospar/Arc2Face

โ–ช Project: https://arc2face.github.io

โ–ช Demo: https://huggingface.co/spaces/FoivosPar/Arc2Face

โ–ช Paper: https://arxiv.org/abs/2403.11641

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๐Ÿ“ Recent Advances in Generative Adversarial Networks for Gene Expression Data: A Comprehensive Review

๐Ÿ“• Journal: Mathematics (I.F.=2.4)
๐Ÿ—“ Publish year: 2023

๐Ÿง‘โ€๐Ÿ’ปAuthors: Minhyeok Lee
๐ŸขUniversity: Chung-Ang University, Republic of Korea

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