LiquidAI/LFM2-2.6B-Exp converted to the LiteRT-LM (.litertlm) format for Google’s LiteRT-LM runtime. Tested on litert-lm 0.18.0 on a Mac; the phone rows ran the prebuilt Android binary named below. On litert-lm 0.17.1 the int8 file answered «What is the capital of France?» as if no question had been asked (one CPU run; the int4 file was not tried on 0.17.1). Liquid AI describes LFM2-2.6B-Exp as an experimental checkpoint built on LFM2-2.6B using pure reinforcement learning, trained on instruction following, knowledge and math, and suggests the LFM2 models for agentic tasks, data extraction, RAG, creative writing and multi-turn conversations rather than knowledge-intensive tasks or programming. Config, tokenizer and chat template match LFM2-2.6B’s: 2,569,272,320 parameters in 30 layers (22 convolution + 8 attention), tied embeddings, a 65,536-token vocabulary, a 32,768-token context (4096 here); English, Arabic, Chinese, French, German, Japanese, Korean and Spanish. Liquid AI’s card says nothing about reasoning, yet in the runs below the model sometimes wrote a trace between and . On GSM8K (n=100) and IFEval-lite (n=120) the two files score within two items of the bf16 model…
Модальности:
Генерация текста
Задача: Генерация текста
Автор: litert-community
Теги: litert-lm, litert, litertlm, on-device, edge, liquid, lfm2
Лайков: 3 | Загрузок: 261
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
