Quantized to Q5KM with importance matrices for higher accuracy. This model is a fine-tuned version of LiquidAI/LFM2.5-8B-A1B, adapted on the angrygiraffe/claude-opus-4.6-4.7-reasoning-8.7k dataset for English text-generation and reasoning-style responses. The fine-tuning run used a custom Convergent Intelligence optimizer stack, CIxOpt, designed for heterogeneous routing across parameter types. The goal of this checkpoint is to test whether a Liquid Foundation Model backbone can be adapted efficiently through targeted sparse participation rather than broad full-model modification. This is an experimental research checkpoint intended for continued evaluation, domain adaptation, and architecture/optimizer testing. — Base: LiquidAI/LFM2.5-8B-A1B — Architecture family: Liquid Foundation Model / hybrid causal language model — Task: Causal language modeling — Language: English — License: Apache 2.0, inherited from the released model metadata unless otherwise restricted by upstream dependencies The dataset was processed into chat-style training examples using tokenizer-compatible chat formatting where available. Empty or malformed examples were filtered before tokenization. This model…
Модальности:
Генерация текста
Области применения:
Логика и рассуждение Диалог / чат
Задача: Генерация текста
Автор: DarkKitsune
Теги: gguf, lfm2_moe, llama.cpp, lfm2.5, lfm2-moe, moe, mixture-of-experts, liquid-ai
Лайков: 3 | Загрузок: 444
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
