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Fireworks AI adds Kimi K2.6 model to its training platform

Fireworks AI has announced the integration of Kimi K2.6, a model from Kimi Moonshot, onto its Training Platform. This integration allows users to leverage the Kimi K2.6 model through Fireworks AI's Managed and Training API workflows. The platform supports various training methods including Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Reinforcement Learning (RL), with options for both smart defaults and custom loss functions, all while supporting a 265K context window. AI

影响 Expands training options for developers using Fireworks AI's platform, enabling fine-tuning of models with large context windows.

排序理由 Integration of a specific model (Kimi K2.6) onto an inference platform, enabling new training capabilities.

在 X — Fireworks (inference infra) 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

Fireworks AI adds Kimi K2.6 model to its training platform

报道来源 [2]

  1. X — Fireworks (inference infra) TIER_1 English(EN) · FireworksAI_HQ ·

    What would you like to see next? Full Param tuning?

    What would you like to see next? Full Param tuning?

  2. X — Fireworks (inference infra) TIER_1 English(EN) · FireworksAI_HQ ·

    Kimi K2.6 from @Kimi_Moonshot is now available on @FireworksAI_HQ Training Platform across the Managed and Training API workflows.

    Kimi K2.6 from @Kimi_Moonshot is now available on @FireworksAI_HQ Training Platform across the Managed and Training API workflows. Try SFT, DPO, RL with smart defaults or your own custom loss function with industry leading 265K context window. https://t.co/jqKuwWWEB0