mlx-lm/ACKNOWLEDGMENTS.md

Individual Contributors

If you wish to be acknowledged for your contributions, please list your name with a short description of your contribution(s) below. For example:

• Jane Smith: Added the foo example.

MLX LM was developed with contributions from the following individuals:

• Shunta Saito: Added support for PLaMo models.
• Gökdeniz Gülmez: Added support for the following architectures: OpenBMB's MiniCPM and MiniCPM3, Kyutai's Helium, State-Space's Mamba v1, Mamba v2, Z.ai & THUKEG's GLM, GLM4, Rednote dots.llm1, Baisu's Ernie4.5 MoE, inclusionAI's Bailing MoE e.g. Ling-family, Klear team - Kuaishou Technology's Klear, IBM's Granite MoE, Meituan's LongCat, Nvidia's Nemotron H, Swiss-AI's Apertus, Nikity's Lille130m, Alibaba Qwen's Qwen3Next, and Allenai's OLMoE; Helped add support for the following model architectures: Alibaba Qwen's Qwen3 & Qwen3MoE); Added support for the following training algorithms: Full Weight Fine-Tuning, and the Muon optimizer; Added support for the following other features: Multiple Optimizers to choose for training, and reporting training metrics to WandB (Weights & Biases).
• Prince Canuma: Helped add support for the following model architectures: HuggingFace's Starcoder2, Cohere's Cohere (1 and 2), Alibaba Qwen's Qwen (2, 3 and MoE), Microsoft's Phi (3 and 3.5 MoE), BitNet1.58, Meta's Llama (3 and 4), Google DeepMind's Gemma 3, and InterLM's InternLM 2.5.