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Llama 3 released
Meta has released the new SOTA Llama 3 in two versions for 8B and 70B parameters.
Context length 8K, support 30 languages.
โข HF : https://huggingface.co/spaces/ysharma/Chat_with_Meta_llama3_8b
โข Blog : https://ai.meta.com/blog/meta-llama-3/
You can test
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โก๏ธ Graph Machine Learning
Free advanced course: Machine learning on graphs .
The course is regularly supplemented with practical problems and slides. The author Xavier Bresson is a professor at the National University of Singapore.
โช Introduction
โช Dive into graphs
- Lab1: Generate LFR social networks
https://github.com/xbresson/GML2023/blob/main/codes/02_Graph_Science/code01.ipynb
- Lab2: Visualize spectrum of point cloud & grid
https://github.com/xbresson/GML2023/blob/main/codes/02_Graph_Science/code02.ipynb
- Lab3/4: Graph construction for two-moon & text documents
https://github.com/xbresson/GML2023/blob/main/codes/02_Graph_Science/code03.ipynb
https://github.com/xbresson/GML2023/blob/main/codes/02_Graph_Science/code04.ipynb
โช Graph clustering
- Lab1: k-means
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code01.ipynb
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code02.ipynb
- Lab2: Metis
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code03.ipynb
- Lab3/4: NCut/PCut
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code04.ipynb
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code05.ipynb
- Lab5: Louvain
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code06.ipynb
https://pic.twitter.com/vSXCx364pe
โช Lectures 4 Graph SVM
- Lab1 : Standard/Linear SVM
https://github.com/xbresson/GML2023/blob/main/codes/04_Graph_SVM/code01.ipynb
- Lab2 : Soft-Margin SVM
https://github.com/xbresson/GML2023/blob/main/codes/04_Graph_SVM/code02.ipynb
- Lab3 : Kernel/Non-Linear SVM
https://github.com/xbresson/GML2023/blob/main/codes/04_Graph_SVM/code03.ipynb
- Lab4 : Graph SVM
https://github.com/xbresson/GML2023/blob/main/codes/04_Graph_SVM/code04.ipynb
Running instructions: https://storage.googleapis.com/xavierbresson/lectures/CS6208/running_notebooks.pdf
๐ก Github
โ
https://t.me/DataScienceT
Free advanced course: Machine learning on graphs .
The course is regularly supplemented with practical problems and slides. The author Xavier Bresson is a professor at the National University of Singapore.
โช Introduction
โช Dive into graphs
- Lab1: Generate LFR social networks
https://github.com/xbresson/GML2023/blob/main/codes/02_Graph_Science/code01.ipynb
- Lab2: Visualize spectrum of point cloud & grid
https://github.com/xbresson/GML2023/blob/main/codes/02_Graph_Science/code02.ipynb
- Lab3/4: Graph construction for two-moon & text documents
https://github.com/xbresson/GML2023/blob/main/codes/02_Graph_Science/code03.ipynb
https://github.com/xbresson/GML2023/blob/main/codes/02_Graph_Science/code04.ipynb
โช Graph clustering
- Lab1: k-means
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code01.ipynb
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code02.ipynb
- Lab2: Metis
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code03.ipynb
- Lab3/4: NCut/PCut
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code04.ipynb
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code05.ipynb
- Lab5: Louvain
https://github.com/xbresson/GML2023/blob/main/codes/03_Graph_Clustering/code06.ipynb
https://pic.twitter.com/vSXCx364pe
โช Lectures 4 Graph SVM
- Lab1 : Standard/Linear SVM
https://github.com/xbresson/GML2023/blob/main/codes/04_Graph_SVM/code01.ipynb
- Lab2 : Soft-Margin SVM
https://github.com/xbresson/GML2023/blob/main/codes/04_Graph_SVM/code02.ipynb
- Lab3 : Kernel/Non-Linear SVM
https://github.com/xbresson/GML2023/blob/main/codes/04_Graph_SVM/code03.ipynb
- Lab4 : Graph SVM
https://github.com/xbresson/GML2023/blob/main/codes/04_Graph_SVM/code04.ipynb
Running instructions: https://storage.googleapis.com/xavierbresson/lectures/CS6208/running_notebooks.pdf
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A quick guide on how to set up your new Llama 3 8B with ORPO .
I hope you will enjoy!
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๐ฆพ ๐ฆ Power of matplotlib
This beauty can be made using matplotlib . This is a visualization of an engraving by the German artist Albrecht Dรผrer, depicting an Indian rhinoceros, as the artist imagined it from the descriptions and drawings available to him in 1515.
Want to learn the same thing: here's a cool free book: " Scientific Visualization: Python + Matplotlib "
The sources of the book with code examples are here .
โช Poster
โช Book
โช Code from the book
โ
https://t.me/DataScienceT
This beauty can be made using matplotlib . This is a visualization of an engraving by the German artist Albrecht Dรผrer, depicting an Indian rhinoceros, as the artist imagined it from the descriptions and drawings available to him in 1515.
Want to learn the same thing: here's a cool free book: " Scientific Visualization: Python + Matplotlib "
The sources of the book with code examples are here .
โช Poster
โช Book
โช Code from the book
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๐ Study the paper
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SAM + Optical Flow = FlowSAM
FlowSAM is a new tool for detecting and segmenting moving objects in video, which significantly outperforms all previous models , both for a single object and for multiple objects
โช Project page: https://www.robots.ox.ac.uk/~vgg/research/flowsam/
โช Code: https://github.com/video2game/video2game
โช Paper: https://arxiv.org/abs/2404.12389
โช Data: https://drive.google.com/drive/folders/1tmDq_vG_BvY5po40Ux5OBds1avUM_CbR
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๐ Study the paper
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OpenVoice V2 is a new version of the open text-to-speech model that allows you to clone any voice and generate speech in various languages.
โข Github: https://github.com/myshell-ai/OpenVoice/tree/main
โข Usage: https://github.com/myshell-ai/OpenVoice/blob/main/docs/USAGE.md
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A new training-free method that improves the performance of pre-trained diffusion models.
It can be integrated into diffusion pipelines by adding just one line of code!
pip3 install hidiffusionโข page : https://hidiffusion.github.io
โข paper : https://arxiv.org/abs/2311.17528
โข code : https://github.com/megvii-research/HiDiffusion
โข colab : https://colab.research.google.com/drive/1EiBn9lSnPZTU4cikRRaBBexs429M-qty?usp=sharing
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Massachusetts Institute of Technology introduced FlowMap.
This is a new comprehensive differentiable method for reconstructing a 3D scene , which allows you to accurately specify camera angles, motion characteristics and video depth for each frame.
FlowMap allows you to create realistic 360ยฐ views.
โข Github: https://github.com/dcharatan/flowmap
โข Paper: https://arxiv.org/abs/2404.15259
โข Dataset: https://drive.google.com/drive/folders/1PqByQSfzyLjfdZZDwn6RXIECso7WB9IY
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OpenBioLLM-Llama3-70B and 8B: the most effective and affordable Lms in the medical field today!
Outperforms industry giants like GPT-4, Gemini, Meditron-70B, Med-PaLM-1 and Med-PaLM-2 in the biomedical field.
The OpenBioLLM-70B reaches SOTA and is a new achievement for models of this size.
The OpenBioLLM-8B even outperforms GPT-3.5, Gemini and Meditron-70B!
- 70B : https://huggingface.co/aaditya/OpenBioLLM-Llama3-70B
- 8B : https://huggingface.co/aaditya/OpenBioLLM-Llama3-8B
- Medical Leaderboard : https://huggingface.co/spaces/openlifescienceai/open_medical_llm_leaderboard
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