π Fast Segment Anything
Fast Segment Anything Model reaches comparable performance with the SAM method at 50 times higher run-time speed.
git clone https://github.com/CASIA-IVA-Lab/FastSAM.git
π₯ Github: https://github.com/casia-iva-lab/fastsam
βοΈ Demo:https://huggingface.co/spaces/An-619/FastSAM
π Paper: https://arxiv.org/pdf/2306.12156.pdf
πDataset: https://paperswithcode.com/dataset/sa-1b
https://t.iss.one/DataScienceT
Fast Segment Anything Model reaches comparable performance with the SAM method at 50 times higher run-time speed.
git clone https://github.com/CASIA-IVA-Lab/FastSAM.git
π₯ Github: https://github.com/casia-iva-lab/fastsam
βοΈ Demo:https://huggingface.co/spaces/An-619/FastSAM
π Paper: https://arxiv.org/pdf/2306.12156.pdf
πDataset: https://paperswithcode.com/dataset/sa-1b
https://t.iss.one/DataScienceT
π7β€βπ₯2β€1
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βοΈ LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models
Extensible and lightweight toolkit, LMFlow, which aims to simplify the finetuning and inference of general large foundation models.
π₯ Github: https://github.com/optimalscale/lmflow
βοΈ Demo: https://lmflow.com/
π Paper: https://arxiv.org/abs/2306.12420v1
πDataset: https://paperswithcode.com/dataset/pubmedqa
Official channel:
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Extensible and lightweight toolkit, LMFlow, which aims to simplify the finetuning and inference of general large foundation models.
π₯ Github: https://github.com/optimalscale/lmflow
βοΈ Demo: https://lmflow.com/
π Paper: https://arxiv.org/abs/2306.12420v1
πDataset: https://paperswithcode.com/dataset/pubmedqa
Official channel:
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CBOGlobalConvergenceAnalysis
π₯ Github: https://github.com/efficienttraining/labelbench
β© Paper: https://arxiv.org/pdf/2306.09778v1.pdf
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π₯ Github: https://github.com/efficienttraining/labelbench
β© Paper: https://arxiv.org/pdf/2306.09778v1.pdf
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β€2
Automatically find issues in image datasets and practice data-centric computer vision.
CleanVision automatically detects potential issues in image datasets like images that are: blurry, under/over-exposed, (near) duplicates, etc. This data-centric AI package is a quick first step for any computer vision project to find problems in the dataset, which you want to address before applying machine learning. CleanVision is super simple -- run the same couple lines of Python code to audit any image dataset!
https://github.com/cleanlab/cleanvision
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CleanVision automatically detects potential issues in image datasets like images that are: blurry, under/over-exposed, (near) duplicates, etc. This data-centric AI package is a quick first step for any computer vision project to find problems in the dataset, which you want to address before applying machine learning. CleanVision is super simple -- run the same couple lines of Python code to audit any image dataset!
https://github.com/cleanlab/cleanvision
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The Attention Mechanism from Scratch
https://machinelearningmastery.com/the-attention-mechanism-from-scratch/
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Introduction to Computer Architecture, IIT Delhi
π Free Online Course
π» 38 Lecture Videos
β° 1 Module
πββοΈ Self paced
Teacher π¨βπ« : Prof. Anshul Kumar
π https://nptel.ac.in/courses/106102062
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π Free Online Course
π» 38 Lecture Videos
β° 1 Module
πββοΈ Self paced
Teacher π¨βπ« : Prof. Anshul Kumar
π https://nptel.ac.in/courses/106102062
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π₯ Awesome-Multimodal-Large-Language-Models
Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.
π₯ Github: https://github.com/bradyfu/awesome-multimodal-large-language-models
π Paper: https://arxiv.org/abs/2306.13394v1
πDataset: https://paperswithcode.com/dataset/coco
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Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.
π₯ Github: https://github.com/bradyfu/awesome-multimodal-large-language-models
π Paper: https://arxiv.org/abs/2306.13394v1
πDataset: https://paperswithcode.com/dataset/coco
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β€βπ₯3β€1
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π Machine Learning Cheat Sheets
https://sites.google.com/view/datascience-cheat-sheets
Machine Learning Animations: https://sites.google.com/view/mlingifs#h.341bzfgiuxfx
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https://sites.google.com/view/datascience-cheat-sheets
Machine Learning Animations: https://sites.google.com/view/mlingifs#h.341bzfgiuxfx
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π2β€βπ₯1β€1
β‘ LightGlue. Local Feature Matching at Light Speed
LightGlue a lightweight feature matcher with high accuracy and adaptive pruning techniques, both in the width and depth of the network, for blazing fast inference.
π₯ Github: https://github.com/cvg/lightglue
π Paper: https://arxiv.org/abs/2306.13643v1
πDataset: https://paperswithcode.com/dataset/hpatches
https://t.iss.one/DataScienceT
LightGlue a lightweight feature matcher with high accuracy and adaptive pruning techniques, both in the width and depth of the network, for blazing fast inference.
git clone https://github.com/cvg/LightGlue.git && cd LightGlue
python -m pip install -e .
π₯ Github: https://github.com/cvg/lightglue
π Paper: https://arxiv.org/abs/2306.13643v1
πDataset: https://paperswithcode.com/dataset/hpatches
https://t.iss.one/DataScienceT
β€2π2
This channel is for Programmers, Coders, Software Engineers.
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
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1- Data Science
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5- Data Analysis
6- Statistics
7- Deep Learning
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This channel is for Programmers, Coders, Software Engineers.
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
Cross promotion and ads: @hussein_sheikho
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πΆββοΈ MotionGPT: Human Motion
as Foreign Language
MotionGPT consists of a motion tokenizer responsible for converting raw motion data into discrete motion tokens, as well as a motion-aware language model that learns to understand the motion tokens from large language pre-training models by corresponding textual descriptions.
β© Project: https://motion-gpt.github.io/
π₯ Github: https://github.com/openmotionlab/motiongpt
π Paper: https://arxiv.org/pdf/2306.14795.pdf
πDataset: https://paperswithcode.com/dataset/amass
https://t.iss.one/DataScienceT
as Foreign Language
MotionGPT consists of a motion tokenizer responsible for converting raw motion data into discrete motion tokens, as well as a motion-aware language model that learns to understand the motion tokens from large language pre-training models by corresponding textual descriptions.
β© Project: https://motion-gpt.github.io/
π₯ Github: https://github.com/openmotionlab/motiongpt
π Paper: https://arxiv.org/pdf/2306.14795.pdf
πDataset: https://paperswithcode.com/dataset/amass
https://t.iss.one/DataScienceT
β€βπ₯2β€2π1
π₯ Free Courses on Large Language Models
βͺChatGPT Prompt Engineering for Developers
βͺLangChain for LLM Application Development
βͺBuilding Systems with the ChatGPT API
βͺGoogle Cloud Generative AI Learning Path
βͺIntroduction to Large Language Models with Google Cloud
βͺLLM University
βͺFull Stack LLM Bootcamp
https://t.iss.one/DataScienceT
βͺChatGPT Prompt Engineering for Developers
βͺLangChain for LLM Application Development
βͺBuilding Systems with the ChatGPT API
βͺGoogle Cloud Generative AI Learning Path
βͺIntroduction to Large Language Models with Google Cloud
βͺLLM University
βͺFull Stack LLM Bootcamp
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β€βπ₯5β€3π1
PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and Aggregation
π₯ Github: https://github.com/jieqianyu/panet
β© Paper: https://arxiv.org/pdf/2306.15348v1.pdf
π¨ Dataset: https://paperswithcode.com/dataset/kitti
https://t.iss.one/DataScienceT
π₯ Github: https://github.com/jieqianyu/panet
β© Paper: https://arxiv.org/pdf/2306.15348v1.pdf
π¨ Dataset: https://paperswithcode.com/dataset/kitti
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π3β€βπ₯1β€1
π¬ 3D-Speaker: A Large-Scale Multi-Device, Multi-Distance, and Multi-Dialect Corpus for Speech Representation Disentanglement
A large-scale speech corpus to facilitate the research of speech representation
π₯ Github: https://github.com/alibaba-damo-academy/3D-Speaker
π Paper: https://arxiv.org/abs/2306.15354v1
πDataset: https://3dspeaker.github.io/
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A large-scale speech corpus to facilitate the research of speech representation
π₯ Github: https://github.com/alibaba-damo-academy/3D-Speaker
π Paper: https://arxiv.org/abs/2306.15354v1
πDataset: https://3dspeaker.github.io/
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β€1β€βπ₯1π1
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What the Brain Sees
How a text-to-image model generates images from brain scans
https://www.deeplearning.ai/the-batch/how-a-text-to-image-model-generates-images-from-brain-scans/
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How a text-to-image model generates images from brain scans
https://www.deeplearning.ai/the-batch/how-a-text-to-image-model-generates-images-from-brain-scans/
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β€1β€βπ₯1π1
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The source code for DragGAN has been released! π₯π₯π₯
We can finally play with that marvel!
π GitHub repository: https://github.com/XingangPan/DragGAN
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We can finally play with that marvel!
π GitHub repository: https://github.com/XingangPan/DragGAN
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β€βπ₯4π1
π Constrained-Text-Generation-Studio
AI writing assistant for recreational linguists, poets, creative writers, and/or researchers to use and study the ability of large-scale language models.
π₯ Github: https://github.com/hellisotherpeople/constrained-text-generation-studio
π Paper: https://arxiv.org/abs/2306.15926v1
πDataset: https://huggingface.co/datasets/Hellisotherpeople/Lipogram-e
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AI writing assistant for recreational linguists, poets, creative writers, and/or researchers to use and study the ability of large-scale language models.
π₯ Github: https://github.com/hellisotherpeople/constrained-text-generation-studio
π Paper: https://arxiv.org/abs/2306.15926v1
πDataset: https://huggingface.co/datasets/Hellisotherpeople/Lipogram-e
https://t.iss.one/DataScienceT
π3