# Low-resource quantization

A large language model with 24B parameters based on the Mistral architecture, optimized for role-playing and creative writing, using the GGUF quantization format

Weighted/matrix quantized model of Qwen2-Audio-7B-Instruct, supporting English audio-to-text transcription tasks

Based on andrewzh's Absolute_Zero_Reasoner-Coder-14b model, this is a version quantized using llama.cpp's imatrix, suitable for reasoning and code generation tasks.

Quantized version based on webbigdata/gemma-2-2b-jpn-it-translate, focusing on translation tasks between Japanese and English

A 3B-parameter large language model based on the Llama3.2 architecture, supporting English text generation tasks, quantized using llama.cpp with imatrix

This is the quantized version of the c4ai-command-r7b-12-2024-abliterated model, quantized using llama.cpp, supporting multiple quantization types and suitable for various hardware environments.

Tango-70B-Instruct is a large language model designed to enhance language performance in Spanish-speaking regions.

Meta-Llama-3.1-405B-Instruct is a large language model with 405 billion parameters based on the Llama 3.1 architecture, optimized for instruction-following tasks and supporting multiple languages.

A 3B-parameter language model based on the Mamba architecture, focused on efficient text generation tasks

PersianMind is a cross-lingual Persian-English large language model developed by the University of Tehran team, excelling in multiple Persian language tasks.