ML Research Hub – Telegram
ML Research Hub
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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

Admin: @HusseinSheikho || @Hussein_Sheikho
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🎁 Lisa has given away over $100,000 in the last 30 days. Every single one of her subscribers is making money.

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https://news.1rj.ru/str/+XYNujpT_-Ns2OGI5
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InterpreTabNet: Distilling Predictive Signals from Tabular Data by Salient Feature Interpretation

🖥 Github: https://github.com/jacobyhsi/InterpreTabNet

📕 Paper: https://arxiv.org/abs/2406.00426v1

https://news.1rj.ru/str/DataScienceT
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☄️ Qwen2 is the coolest release of open LLMs since Llama 3!

Alibaba has just released their new family of multilingual models that outperform the Llama 3 in many ways.

🤯 Qwen2 is released in 5 sizes, trained in 29 languages!

5️⃣ Sizes: 0.5B, 1.5B, 7B, 57B-14B (MoE), 72B.
✔️ Context: 32k for 0.5B & 1.5B, 64k for 57B MoE, 128k for 7B & 72B
Supports 29 languages.
🟢 Released under the Apache 2.0 license, except for version 72B.

🔖 BLOG: https://qwenlm.github.io/blog/qwen2/

🤗 HF collection: https://huggingface.co/collections/Qwen/qwen2-6659360b33528ced941e557f

🤖 https://modelscope.cn/organization/qwen

👨‍💻 GitHub: https://github.com/QwenLM/Qwen2

https://news.1rj.ru/str/DataScienceT
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Flash Diffusion - acceleration of any diffusion model for image generation in a few steps

This is the name of the work recently published by Clément Chadebec, Onur Tasar and their colleagues.
This is a distillation method for creating fast diffusion patterns.
When training the model using this method on the COCO2014 and COCO2017 datasets, the FID and CLIP-Score achieve good values; it requires only a few hours of training on the GPU and fewer model parameters than existing methods require.

🟡 Flash Diffusion page
🖥 GitHub

🤗 Flash SD
🤗 Flash SDXL

https://news.1rj.ru/str/DataScienceT
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🚀 AgentGym: Evolving Large Language Model-based Agents across Diverse Environments

🖥 Github: https://github.com/woooodyy/agentgym

🔖 Paper: https://arxiv.org/abs/2406.04151v1

☄️ Project: https://agentgym.github.io/

✔️ Model (AgentEvol-7B): https://huggingface.co/AgentGym/AgentEvol-7B

https://news.1rj.ru/str/DataScienceT
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🎁 Lisa has given away over $100,000 in the last 30 days. Every single one of her subscribers is making money.

She is a professional trader and broadcasts her way of making money trading on her channel EVERY subscriber she has helped, and she will help you.

🧠 Do this and she will help you earn :

1. Subscribe to her channel
2. Write “GIFT” to her private messages
3. Follow her channel and trade with her. Repeat transactions after her = earn a lot of money.

Subscribe 👇🏻
https://news.1rj.ru/str/+VwDs29eEzRA5MTAx
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L-MAGIC: Language Model Assisted Generation of Images with Coherence

The new Intel- L-MAGIC model can generate high-quality panoramic scenes based on a single input image and text prompt!

Numerous tests show that the model generates panoramic scenes with better scene placement and rendering quality than similar models.

▪️Github: https://github.com/IntelLabs/MMPano
▪️Paper: https://arxiv.org/abs/2406.01843
▪️Project: https://zhipengcai.github.io/MMPano/
▪️Video: https://youtu.be/XDMNEzH4-Ec

https://news.1rj.ru/str/DataScienceT
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🎙 VALLEY 2: Neural Codec Language Models are Human Parity Zero-Shot Text to Speech Synthesizers

In this article, Microsoft introduced VALL-E 2, the latest advancement in language models , which marks a major milestone in text-to-speech (TTS) synthesis, reaching the human level for the first time.

Experiments with LibriSpeech and VCTK datasets have shown that VALL-E 2 outperforms all previous models in terms of generated speech quality and naturalness.

Details: https://arxiv.org/abs/2406.05370
🔴 Demo of VALLE 2 will be available here: https://www.bing.com/?ref=aka&shorturl=valle2

https://news.1rj.ru/str/DataScienceT
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⭐️ New Dream Machine video generator from Luma AI.

Unlike Sora or KLING, it is available for testing.


You can try it here: https://lumalabs.ai/dream-machine

https://news.1rj.ru/str/DataScienceT
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🌟 MusicGPT is an application for running music-generating models locally

- brew install gabotechs/taps/musicgpt

MusicGPT allows you to run the latest music generation models locally on any platform, without installing heavy dependencies such as ML frameworks.

Currently, MusicGPT only supports MusicGen from Meta, but there are plans to add even more different music generation models.

Quick start with Docker:
docker run -it --gpus all -p 8642:8642 -v ~/.musicgpt:/root/.local/share/musicgpt gabotechs/musicgpt --gpu --ui-expose

or using cargo:
cargo install musicgpt

🖥 GitHub

https://news.1rj.ru/str/DataScienceT
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