Telegram Web Link
👩‍💻 Julia Programming Language for Biologists





📎 Study the paper


@Machine_learn
3👍1
O1 Replication Journey -- Part 2: Surpassing O1-preview through Simple Distillation, Big Progress or Bitter Lesson?

🖥 Github: https://github.com/gair-nlp/o1-journey

📕 Paper: https://arxiv.org/abs/2411.16489v1

🌟 Dataset: https://paperswithcode.com/dataset/lima

💠@Machine_learn
Please open Telegram to view this post
VIEW IN TELEGRAM
3
📖 Penn State University's "Graph Theory"


📌 Lectures

@Machine_learn
4👍4
ShowUI is a lightweight vision-language-action model for GUI agents.

🖥 Github: https://github.com/showlab/showui

📕 Paper: https://arxiv.org/abs/2411.17465v1

🌟 Dataset: https://huggingface.co/datasets/showlab/ShowUI-desktop-8K

@Machine_learn
Please open Telegram to view this post
VIEW IN TELEGRAM
1
📖 General Relativity

📌 Book

@Machine_learn
2
⚡️ Biggest open text dataset release of the year: SmolTalk is a 1M sample big synthetic dataset that was used to train SmolLM v2.

TL;DR;
🧩 New datasets: Smol-Magpie-Ultra (400K) for instruction tuning; Smol-contraints (36K) for precise output; Smol-rewrite (50K) & Smol-summarize (100K) for rewriting and summarization.
🤝 Public Dataset Integrations: OpenHermes2.5 (100K), MetaMathQA & NuminaMath-CoT, Self-Oss-Starcoder2-Instruct, LongAlign & SystemChats2.0
🥇 Outperforms the new Orca-AgenInstruct 1M when trained with 1.7B and 7B models
🏆 Outperform models trained on OpenHermes and Magpie Pro on IFEval and MT-Bench
distilabel to generate all new synthetic datasets
🤗 Released under Apache 2.0 on huggingface

Apache 2.0

Synthetic generation pipelines and training code released.

Dataset: https://huggingface.co/datasets/HuggingFaceTB/smoltalk
Generation Code: https://github.com/huggingface/smollm
Training Code: https://github.com/huggingface/alignment-handbook/tree/main/recipes/smollm2

@Machine_learn
2
Machine learning books and papers pinned «fmri alzheimer's disease classification target journal:https://www.sciencedirect.com/journal/computerized-medical-imaging-and-graphics نفر ٣ رو كم داريم. نيازمند كسي هستيم كه بتونه هزينه سرور رو پرداخت كنه . @Raminmousa @Machine_learn https://www.tg-me.com/+SP9l58Ta_zZmYmY0»
Gaussian Processes for Machine Learning

📚 link

@Machine_learn
Please open Telegram to view this post
VIEW IN TELEGRAM
3
📃Deep learning approaches for non-coding genetic variant effect prediction: current progress and future prospects

📎 Study the paper

@Machine_learn
3👍2
📚 Deep Learning with Python Develop Deep Learning Models on Theano and TensorFLow Using Keras by Jason Brownlee

🔗 Book


@Machine_learn
3🔥2
📚 Machine learning mastery

🔗 Github


@Machine_learn
3
فقط جايگاه ٣ باقي مونده...!
Super beginner-friendly book on Linear Algebra

🔗 Book

@Machine_learn
2
⭐️ Region-Aware Text-to-Image Generation via Hard Binding and Soft Refinement

RAG-Diffusion now supports FLUX.1 Redux!

🔥 Ready to take control? Customize your region-based images with our training-free solution and achieve powerful, precise results!

🔗 Code: https://github.com/NJU-PCALab/RAG-Diffusion

@Machine_learn
Please open Telegram to view this post
VIEW IN TELEGRAM
2025/07/08 21:03:09
Back to Top
HTML Embed Code: