GGUF quantized versions of LiquidAI/LFM2.5-2.6B, a high-performance hybrid model designed for on-device deployment, featuring a 128K context window and advanced agentic capabilities. LFM2.5-2.6B is part of the LFM2.5 family, building on the LFM2 architecture to provide best-in-class performance for its size. It is specifically optimized for agentic workloads, tool use, and long-context workflows, offering competitive performance against models 4x its size. Key features include: — Agentic Post-Training: Trained using agentic reinforcement learning for improved tool use and instruction following. — Efficient Inference: Designed for high-speed execution on both CPU and GPU. — Reasoning Capabilities: A pure reasoning model that utilizes a tag to reason before answering. — Massive Context: Supports up to 131,072 tokens. LFM2.5 uses a ChatML-like format. It is a reasoning model that automatically adds a tag when starting an assistant answer to process its logic before providing the final response. LFM2.5 supports Pythonic function calling. It outputs function calls between and tokens. These GGUF files were created using llama.cpp tools to enable efficient local deployment on CPUs…
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Автор: WhiskyAKM
Теги: llama-cpp, gguf, liquid, lfm2.5, quantized, conversational, endpoints_compatible
Лайков: 3 | Загрузок: 61
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
