Chen Qin
chenqin
Delivery Content Infra @Pinterest
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116AI agents running research on single-GPU nanochat training automatically
No description provided.
Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞
Vitess is a database clustering system for horizontal scaling of MySQL. This fork does not contain interesting changes - it's mostly the placeholder for PRs that PlanetScale maintainers cooperate on
Apache Spark - A unified analytics engine for large-scale data processing
lightweight HPC data processing framework
Mirror of Apache Flink
A Model Context Protocol server for Excel file manipulation
Chrome DevTools for coding agents
No description provided.
A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
Lightweight MCP Server for Computer Use in Windows
Blazing-fast query execution engine speaks Apache Spark language and has Arrow-DataFusion at its core.
Collective communications library with various primitives for multi-machine training.
Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.
Gluten: Plugin to Double SparkSQL's Performance
A Scala API for Cascading
A C++ vectorized database acceleration library aimed to optimizing query engines and data processing systems.
All development now happens over here: https://github.com/cwensel/cascading. Cascading is a feature rich API for defining and executing complex and fault tolerant data processing workflows on various cluster computing platforms.
Inference code for LLaMA models
CDC Connectors for Apache Flink®
Cascading on Apache Flink®
Notes talking about the design and implementation of Apache Spark
Transformer-based Realtime User Action Model for Recommendation at Pinterest
Apache Arrow DataFusion Python Bindings
A cross platform way to express data transformation, relational algebra, standardized record expression and plans.
Highly optimized versions of memmove, memcpy, memset, and memcmp supporting SSE4.2, AVX, AVX2, and AVX512
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Running large language models like OPT-175B/GPT-3 on a single GPU. Focusing on high-throughput generation.