# Multi-precision quantization

A static quantization version of UniReason-Qwen3-14B-RL, suitable for text generation and mathematical reasoning research scenarios.

This project provides the GGUF quantized file for the Echelon-AI/Med-Qwen2-7B model, supported by Featherless AI, aiming to enhance model performance and reduce operating costs.

This project provides optimized GGUF quantized files, which can significantly improve model performance. These quantized files are supported by Featherless AI. Users can run any desired model by paying a small fee.

DeepSeek-R1-0528 is a large language model that has been quantized to optimize its running efficiency on different hardware.

Llamacpp imatrix quantized version based on a-m-team/AM-Thinking-v1 model, supporting multiple quantization types, suitable for text generation tasks.

Llama 2 is a 7B-parameter large language model developed by Meta, offering multiple quantization versions to accommodate different hardware requirements.

Lacia_sum_small_v1 is a statically quantized model based on the T5 architecture, primarily designed for text summarization tasks. It supports Russian and English, making it suitable for natural language processing applications.

GIGABATEMAN-7B is a 7B-parameter large language model based on the Mistral architecture, focusing on text generation tasks.

Xwin-LM 13B V0.1 is a large language model based on the Llama2 architecture, developed by the Xwin-LM team. The model responds to user queries in a professional, detailed, and courteous manner, making it suitable for conversational scenarios.