de47734510
* initial commit * update tuner/utils.py * update ACKNOWLEDGMENTS.md * update * nits * movinf mamba2 cache over to cache.py + clean up * clean up * fix residual_in_fp32 * updates * adding default args * updates * first working inference with codestral mamba * clean up * adding 1b mamba 2 * udpdates * updates * updates * finish * clean up * clean ups * format * nits * adding some einsums * format again * optimize + format * nits * nits * more speed * use custom kernel * update * format * nits --------- Co-authored-by: Awni Hannun <[email protected]>
25 lines
1.5 KiB
Markdown
25 lines
1.5 KiB
Markdown
# Individual Contributors
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If you wish to be acknowledged for your contributions, please list your name
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with a short description of your contribution(s) below. For example:
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- Jane Smith: Added the `foo` example.
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MLX LM was developed with contributions from the following individuals:
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- Shunta Saito: Added support for PLaMo models.
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- Gökdeniz Gülmez: Added support for the following architectures: OpenBMB's
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`MiniCPM` and `MiniCPM3`, Kyutai's `Helium`, State-Space's `Mamba v1`, `Mamba v2`, Z.ai &
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THUKEG's `GLM`, `GLM4`, Rednote `dots.llm1`, Baisu's `Ernie4.5 MoE`, inclusionAI's
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`Bailing MoE e.g. Ling-family`, Klear team - Kuaishou Technology's `Klear`,
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IBM's `Granite MoE`, Meituan's `LongCat`, Nvidia's `Nemotron H`, Swiss-AI's
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`Apertus`, Nikity's `Lille130m`, Alibaba Qwen's `Qwen3Next`, and Allenai's `OLMoE`;
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Helped add support for the following model architectures: Alibaba Qwen's `Qwen3 & Qwen3MoE)`;
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Added support for the following training algorithms: `Full Weight Fine-Tuning`, and the `Muon`
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optimizer; Added support for the following other features: `Multiple Optimizers
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to choose for training`, and `reporting training metrics to WandB (Weights & Biases)`.
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- Prince Canuma: Helped add support for the following model architectures:
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HuggingFace's `Starcoder2`, Cohere's `Cohere (1 and 2)`, Alibaba Qwen's `Qwen
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(2, 3 and MoE)`, Microsoft's `Phi (3 and 3.5 MoE)`, `BitNet1.58`, Meta's `Llama
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(3 and 4)`, Google DeepMind's `Gemma 3`, and InterLM's `InternLM 2.5`.
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