Website cyan.kiwi Models Hugging Face · ModelScope Connect X · Reddit · Email Version cyankiwi 26.05.01 Calibration STEM and Agentic Model Size 23.07 GB — Training: pre-training, post-training and reinforcement learning stages — Number of parameters: 33B total with 3B activated per token — Optimizer: Muon — Layers: 40 layers (10 layers with global attention, 30 layers with sliding window attention) — Experts: 256 experts with 1 shared expert — Sliding Window: 512 toke In all cases these were official scores published in release blog posts or equivalent, with the exception of gpt-oss-120b and Claude Haiku 4.5 where the highest published (verified) scores for SWE-Bench Pro and Terminal-Bench 2.0 are from their respective official leaderboards. All benchmarking for Laguna XS 2.1 was completed using Laude Institute’s Harbor Framework with our agent harness, with a maximum of 500 steps and sandboxed execution. The same sampling parameters were used for all…
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Автор: cyankiwi
Теги: laguna, laguna-xs-2.1, vllm, conversational, custom_code, compressed-tensors
Лайков: 3 | Загрузок: 687
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
