Ornith releases 1.5-122B with an expanded self-improvement loop
AI summary
Ornith introduced Ornith-1.5-122B, extending its earlier model by jointly optimizing task generation, scaffold construction, and solution rollouts. The developer says the model continuously creates training tasks, discovers solution strategies, and improves its policy through reinforcement learning, with official and Unsloth GGUF files linked in the announcement.
In-depth insight
The release provides a 122B model based on the developer’s end-to-end self-improvement approach, including continued task, harness, and rollout optimization.
| from Ornith: Ornith-1.5-122B Chirp Chirp! 🐦 We are introducing Ornith-1.5, a major step toward building foundation models through end-to-end self-improvement. Ornith-1.5 extends Ornith-1.0 (which was developed on top of Qwen3.5 and Gemma4 with additional continued pretraining, mid-training, and post-training) by expanding the self-improvement loop from scaffold and rollout optimization to jointly optimizing task generation, scaffold construction, and solution rollouts. Rather than relying on a fixed set of human-curated tasks and manually designed harnesses, Ornith-1.5 continuously generates new training tasks, discovers effective strategies for solving them, and improves the policy through reinforcement learning. For more details on the task, harness, and rollout reward design, please refer to our blog. https://huggingface.co/ornith-ai/Ornith-1.5-122B-GGUF https://huggingface.co/unsloth/Ornith-1.5-122B-GGUF submitted by /u/jacek2023 [link] [comments] |
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