> NeoHorse-1-9B is a 9-billion-parameter causal language model from TokenRhythm, post-trained from Qwen3.5-9B as an initial prototype on the path toward recursive self-improvement (RSI), targeting text-based agent harnesses, tool use, coding, and instruction following. Its core innovation is a routing harness that assigns tasks to a heterogeneous model pool, records tool interactions and outcomes, estimates capability demand, and feeds that signal back into shaping the next training mixture — using routing-guided curriculum SFT and routing-guided on-policy distillation to turn execution trajectories into training data, supported by rigorous deduplication, decontamination, and six-dimensional semantic evaluation of training data. This release contains language-model weights only (vision weights excluded, with configuration and tensor keys repackaged for text-only inference) and retains a 262,144-token native context window extensible to 1,010,000. Across a ten-benchmark evaluation against Granite-4.2-8B, Qwen3.5-9B, Ornith-1.5-9B, Gemma-4-12B-it, and the much larger Muse-Glimmer-30B, NeoHorse-1-9B posts the best overall macro average (69.04 vs. 65.60 for its Qwen3.5-9B base, a…
Модальности:
Генерация текста
Области применения:
Генерация кода Диалог / чат Вызов функций (Tool use)
Задача: Генерация текста
Автор: prithivMLmods
Теги: gguf, text-generation-inference, llama-cpp, agentic, tool-use, coding, reasoning — instruction-following, en
Лайков: 3 | Загрузок: 385
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
