AI is happening. The future is updating.Qwopus3.6-27B-v1-preview-GGUF
As part of the Qwopus series, this release continues the same core direction established in earlier versions: stronger reasoning quality, a more stable answer structure, and less stylistic drift across long-form responses. Instead of introducing a complicated multi-stage design, this preview emphasizes a cleaner and more controlled supervised fine-tuning recipe, with the goal of producing outputs that feel more coherent, deliberate, and aligned across different tasks. > [!TIP] > This model was trained using Unsloth, and the full training workflow runs end-to-end successfully in practice. Many thanks to the Unsloth team for building and maintaining such a practical training stack for open-model fine-tuning. The current version is trained on a mixed reasoning dataset built primarily from `Kassadin88/Claude-Distillation-Dataset`, with additional samples drawn from:
As part of the Qwopus series, this release continues the same core direction established in earlier versions: stronger reasoning quality, a more stable answer structure, and less stylistic drift across long-form responses. Instead of introducing a complicated multi-stage design, this preview emphasizes a cleaner and more controlled supervised fine-tuning recipe, with the goal of producing outputs that feel more coherent, deliberate, and aligned across different tasks. > [!TIP] > This model was trained using Unsloth, and the full training workflow runs end-to-end successfully in practice. Many thanks to the Unsloth team for building and maintaining such a practical training stack for open-model fine-tuning. The current version is trained on a mixed reasoning dataset built primarily from `Kassadin88/Claude-Distillation-Dataset`, with additional samples drawn from: