# Low-resource Quantization

Llamacpp imatrix quantized version based on WhiteRabbitNeo-V3-7B, specializing in cybersecurity and DevOps tasks with code generation support.

QwenStoryteller is a storytelling model based on a vision-language model, focusing on visual narrative and cross-frame consistency.

Clinician-Note-2.0a is a text generation model specialized in the medical field, specifically designed for clinical note and summarization tasks.

This is the result of weighted/importance matrix quantization of the Menlo/Speechless-llama3.2-v0.1 model, offering multiple quantization versions

This is the GGUF quantized version of the Menlo/Ichigo-llama3.1-s-instruct-v0.4 model, designed for speech and language processing tasks in resource-constrained environments.

A statically quantized model based on Menlo/Ichigo-llama3.1-s-instruct-v0.4, offering multiple quantization versions to suit different hardware requirements.

A 7B-parameter merged model with multimodal capabilities, supporting visual functions

GGUF weight files compatible with llama.cpp, supporting dialogue templates and importance matrix quantization.

Astrea-RP-v1-3B is a 3B-parameter large language model that integrates multiple models through task arithmetic, focusing on text generation tasks.