Model Factory

Modelplane is an open-source control-plane product for declaratively deploying and governing self-hosted machine-learning model inference across an organization's GPU fleet, with provider support and networking capabilities for reliable operation across clusters and more complex algorithms.

MiniMind is an open-source tiny large-language-model project and end-to-end training tutorial developed by Jingyao Gong. Its main dense model is approximately 64M parameters, and the repository provides the model architecture, tokenizer, datasets, inference code, and training pipeline. The pipeline covers pretraining, supervised fine-tuning, hand-written LoRA, DPO, PPO, GRPO, CISPO, model distillation, tool calling, adaptive thinking, and agentic reinforcement learning. Core algorithms are implemented directly with native PyTorch rather than relying on high-level abstractions from third-party training libraries. Its agentic reinforcement-learning path performs multi-turn rollouts, executes generated tool calls, appends tool observations to the context, calculates trajectory-level rewards, and updates the policy; rollout can use local PyTorch generation or an SGLang server. MiniMind supports dense and mixture-of-experts variants, single- and multi-GPU training, YaRN-based RoPE length extrapolation, Transformers-format models, and inference through llama.cpp, vLLM, or Ollama. The repository also includes a Streamlit chat interface and a lightweight OpenAI-compatible API server with tool-call and reasoning fields. It is released under the Apache License 2.0.

The Modular Platform is an open-source platform for AI development and deployment, comprising the MAX Framework and the Mojo programming language. Its repository includes the Mojo compiler and standard library, MAX accelerator libraries and kernels, Python-based model pipelines, code examples, and an OpenAI-compatible MAX inference server. The platform supports model serving and AI development while retaining Python-based workflows. The repository is licensed under the Apache License 2.0 with LLVM Exceptions, while MAX usage and distribution are licensed under the Modular Community License.

Apache Spark is a unified analytics engine for large-scale data processing, developed as an Apache project. It provides high-level APIs in Scala, Java, Python, and R, and executes general computation graphs for data analysis. Its higher-level components include Spark SQL and DataFrames, the pandas API on Spark, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. Spark can run locally or submit workloads to clusters through Spark, YARN, or Kubernetes integrations, and is used in large-scale data pipelines such as those underlying Poolside's model factory.