This approach enables efficient inference with large language models (LLMs), achieving up to 20x compression with minimal performance loss. Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, Yuqing Yang and Lili Qiu LongLLMLingua mitigates the 'lost in the middle' issue in LLMs, enhancing long-context information processing.
Explore the resources developed by our community to enhance your experience with Hallo: Thanks to all of them. Join our community and explore these amazing resources to make the most out of Hallo.
figure:: img/mainpage/subscribe.gif :target: https://machinelearningmindset.com/subscription/ Slack Group .. image:: https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat :target: https://github.com/astorfi/Deep-Learning-World/pulls ..
\\\\\ Updated on Feb 6th, 2021: Train Ticket dataset is now available for academic research. You can download from Google Drive or OneDrive.
MuseV was a milestone achieved around July 2023. Amazed by the progress of Sora, we decided to opensource MuseV, hopefully it will benefit the community.
image:: https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat :target: https://github.com/osforscience/deep-learning-all-you-need/pulls .. image:: https://badges.frapsoft.com/os/v2/open-source.png?v=103 :target: https://github.com/ellerbrock/open-source-badge/ ..
😊 EasyAnimate is an end-to-end solution for generating high-resolution and long videos. We can train transformer based diffusion generators, train VAEs for processing long videos, and preprocess metadata.
A Model Context Protocol server that supercharges tools like Claude Code, Codex CLI, and IDE clients such as Cursor or the Claude Dev VS Code extension. PAL MCP connects your favorite AI tool to multiple AI models for enhanced code analysis, problem-solving, and collaborative development.
This project aims at building a universal toolkit for extracting events automatically from documents 📄 (long texts). The details can be found in our paper: Tong Zhu, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Nicholas Yuan, Min Zhang.
The WebUI extension for ControlNet and other injection-based SD controls. This extension is for AUTOMATIC1111's Stable Diffusion web UI, allows the Web UI to add ControlNet to the original Stable Diffusion model to generate images.
AlphaSuite is an open-source quantitative analysis platform that gives you the power to build, test, and deploy professional-grade trading strategies. It's designed for traders and analysts who want to move beyond simple backtests and develop a genuine, data-driven edge in the financial markets.
中文   ｜   English   📖 中文文档   ｜   📖 English Documentation EvalScope is a one-stop LLM evaluation framework built by the ModelScope Community. Just one command to start — it supports model capability evaluation, inference performance stress testing, and result visualization.
Minimal, clean, and well-documented implementations of data structures and algorithms in Python 3. Each file is self-contained with docstrings, type hints, and complexity notes — designed to be read and learned from.
Requires Python 3.10+ or Swarm focuses on making agent coordination and execution lightweight, highly controllable, and easily testable. It accomplishes this through two primitive abstractions: Agents and handoffs.
audio.cpp is a high-performance C++ audio inference framework built on top of ggml, designed to make modern local audio models practical, portable, and fast. Tired of juggling a dozen Conda environments, hundreds of Python packages, and dependency conflicts just to try a few audio models?
You ask a business question, it runs a pipeline of 18 agents that frame the question, explore your data, find the root cause, build a narrative, and hand you a validated slide deck with speaker notes. 18 specialized agents | 39 auto-applied skills | 20 slash commands | DAG-based parallel execution | PDF + HTML export --- This is a tool for analysts, not a replacement for them.
🤗 PEFT State-of-the-art Parameter-Efficient Fine-Tuning (PEFT) methods Fine-tuning large pretrained models is often prohibitively costly due to their scale. Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of large pretrained models to various downstream applications by only fine-tuning a small number of (extra) model parameters instead of all the model's parameters.
Claude Trading Skills started as a personal project to use AI to improve my own trading process. Claude Trading Skills is a Claude Skills-based trading workflow toolkit for time-constrained individual investors.
On commonly used evaluation metrics, ACE-Step v1.5 achieves quality beyond most commercial music models while remaining extremely fast—under 2 seconds per full song on an A100 and under 10 seconds on an RTX 3090. The model runs locally with less than 4GB of VRAM, and supports lightweight personalization: users can train a LoRA from just a few songs to capture their own style.
This project intends to provide a complete description and re-implementation of the WhatsApp Web API, which will eventually lead to a custom client. WhatsApp Web internally works using WebSockets; this project does as well.
This approach enables efficient inference with large language models (LLMs), achieving up to 20x compression with minimal performance loss. Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, Yuqing Yang and Lili Qiu LongLLMLingua mitigates the 'lost in the middle' issue in LLMs, enhancing long-context information processing.
Explore the resources developed by our community to enhance your experience with Hallo: Thanks to all of them. Join our community and explore these amazing resources to make the most out of Hallo.
figure:: img/mainpage/subscribe.gif :target: https://machinelearningmindset.com/subscription/ Slack Group .. image:: https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat :target: https://github.com/astorfi/Deep-Learning-World/pulls ..
\\\\\ Updated on Feb 6th, 2021: Train Ticket dataset is now available for academic research. You can download from Google Drive or OneDrive.
MuseV was a milestone achieved around July 2023. Amazed by the progress of Sora, we decided to opensource MuseV, hopefully it will benefit the community.
image:: https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat :target: https://github.com/osforscience/deep-learning-all-you-need/pulls .. image:: https://badges.frapsoft.com/os/v2/open-source.png?v=103 :target: https://github.com/ellerbrock/open-source-badge/ ..
😊 EasyAnimate is an end-to-end solution for generating high-resolution and long videos. We can train transformer based diffusion generators, train VAEs for processing long videos, and preprocess metadata.
A Model Context Protocol server that supercharges tools like Claude Code, Codex CLI, and IDE clients such as Cursor or the Claude Dev VS Code extension. PAL MCP connects your favorite AI tool to multiple AI models for enhanced code analysis, problem-solving, and collaborative development.
This project aims at building a universal toolkit for extracting events automatically from documents 📄 (long texts). The details can be found in our paper: Tong Zhu, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Nicholas Yuan, Min Zhang.
The WebUI extension for ControlNet and other injection-based SD controls. This extension is for AUTOMATIC1111's Stable Diffusion web UI, allows the Web UI to add ControlNet to the original Stable Diffusion model to generate images.
AlphaSuite is an open-source quantitative analysis platform that gives you the power to build, test, and deploy professional-grade trading strategies. It's designed for traders and analysts who want to move beyond simple backtests and develop a genuine, data-driven edge in the financial markets.
中文   ｜   English   📖 中文文档   ｜   📖 English Documentation EvalScope is a one-stop LLM evaluation framework built by the ModelScope Community. Just one command to start — it supports model capability evaluation, inference performance stress testing, and result visualization.
Minimal, clean, and well-documented implementations of data structures and algorithms in Python 3. Each file is self-contained with docstrings, type hints, and complexity notes — designed to be read and learned from.
Requires Python 3.10+ or Swarm focuses on making agent coordination and execution lightweight, highly controllable, and easily testable. It accomplishes this through two primitive abstractions: Agents and handoffs.
audio.cpp is a high-performance C++ audio inference framework built on top of ggml, designed to make modern local audio models practical, portable, and fast. Tired of juggling a dozen Conda environments, hundreds of Python packages, and dependency conflicts just to try a few audio models?
You ask a business question, it runs a pipeline of 18 agents that frame the question, explore your data, find the root cause, build a narrative, and hand you a validated slide deck with speaker notes. 18 specialized agents | 39 auto-applied skills | 20 slash commands | DAG-based parallel execution | PDF + HTML export --- This is a tool for analysts, not a replacement for them.
🤗 PEFT State-of-the-art Parameter-Efficient Fine-Tuning (PEFT) methods Fine-tuning large pretrained models is often prohibitively costly due to their scale. Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of large pretrained models to various downstream applications by only fine-tuning a small number of (extra) model parameters instead of all the model's parameters.
Claude Trading Skills started as a personal project to use AI to improve my own trading process. Claude Trading Skills is a Claude Skills-based trading workflow toolkit for time-constrained individual investors.
On commonly used evaluation metrics, ACE-Step v1.5 achieves quality beyond most commercial music models while remaining extremely fast—under 2 seconds per full song on an A100 and under 10 seconds on an RTX 3090. The model runs locally with less than 4GB of VRAM, and supports lightweight personalization: users can train a LoRA from just a few songs to capture their own style.
This project intends to provide a complete description and re-implementation of the WhatsApp Web API, which will eventually lead to a custom client. WhatsApp Web internally works using WebSockets; this project does as well.