Fine-tune an 8B model on a 4 GB laptop GPU. Layer streaming keeps the frozen base out of VRAM and feeds it to the GPU one decoder layer at a time. 32 GB.
Global
#837 · +40 · 1d ·GitHub
Build, test, and deploy ML-driven trading strategies — from data sourcing to live execution.
Ragas is your ultimate toolkit for evaluating and optimizing Large Language Model (LLM) applications. Say goodbye to time-consuming, subjective assessments and hello to data-driven, efficient evaluation workflows. Don't have a test dataset ready?
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
#1795 · +15 · 1d ·GitHub
Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
#1875 · +14 · 1d ·GitHub
Register | Course Platform | Course Materials | Join Slack | Course Slack Channel | Telegram | YouTube Playlist | FAQ
#1922 · +13 · 1d ·GitHub
In this course, we'll go from experimentation (design + development) to production (deployment + iteration). We'll do this iteratively by motivating the components that will enable us to build a reliable production system.
#1957 · +13 · 1d ·GitHub
3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses!
#2285 · +10 · 1d ·GitHub
Label Studio is a multi-type data labeling and annotation tool with standardized output format
#2446 · +9 · 1d ·GitHub
MLOps (machine learning operations) is a must-know skill for many data professionals. This free 9-week course teaches the fundamentals of MLOps, from training and experimentation to deployment and monitoring, through structured modules, hands-on workshops, and a final project.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
#2689 · +8 · 1d ·GitHub
Curated list of the best truly open-source AI projects, models, tools, and infrastructure. Daily updated.
Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML.
#2813 · +7 · 1d ·GitHub
This is an open collection of methodologies, tools and step by step instructions to help with successful training and fine-tuning of large language models and multi-modal models and their inference.
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
#3294 · +5 · 1d ·GitHub
Agents Towards Production is your go‑to resource for building production‑ready GenAI agents that scale from prototype to enterprise.
An orchestration platform for the development, production, and observation of data assets.
#3784 · +4 · 1d ·GitHub
Its powerful technical tools start with Expectations: expressive and extensible unit tests for your data. Expectations foster collaboration by giving teams a common language to express data quality tests in an intuitive way.
Data Version Control or DVC is a command line tool and VS Code Extension to help you develop reproducible machine learning projects:
The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.
#4558 · +2 · 1d ·GitHub
The deep learning framework to pretrain and finetune AI models.
#4682 · +2 · 1d ·GitHub
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
#5527 · +1 · 1d ·GitHub
We are happy to announce that we have reached 20,000 stars on GitHub! Thank you for your support and contributions to the Recommenders project. We are excited to continue building and improving this project with your help.
Taipy is designed for data scientists and machine learning engineers to create data & AI driven web applications.
#5688 · +1 · 1d ·GitHub
Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. Argo Workflows is implemented as a Kubernetes CRD (Custom Resource Definition).
Kubeflow is the foundation of tools for AI Platforms on Kubernetes.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.