# Multiple quantization options

This is a quantized version of PinkPixel's Crystal-Think-V2 model, offering multiple quantization types to meet different hardware and performance requirements.

Polaris is an open-source post-training method that uses reinforcement learning to optimize and enhance the model and improve inference capabilities.

Quantize the Menlo/Jan - nano model based on llama.cpp, providing model files of various quantization types to meet different hardware and performance requirements.

Kuvera-8B is an 8B parameter large language model focused on the fields of finance and personal finance, offering multiple quantization versions to meet different hardware requirements.

Jedi-3B-1080p is a 3B-parameter model developed by xlangai, quantized using llama.cpp, suitable for image-text generation tasks.

Skywork-OR1-7B is a 7B-parameter large language model offering multiple quantization versions to accommodate different hardware requirements.

A quantized version of Tessa - Rust - T1 - 7B, quantized using the llama.cpp tool, supporting efficient operation under different hardware conditions.

A quantized version of the arcee-ai/Virtuoso-Small-v2 model based on llama.cpp, offering multiple quantization types to meet different hardware and performance requirements.

A Gemma2 model optimized for novel and story creation, fine-tuned by integrating multiple top-notch story creation models, with more rich, delicate, and in-depth content generation capabilities.

The Llamacpp imatrix quantization version of bagel-8b-v1.0, providing multiple quantization files to meet different hardware and performance requirements.

CodeLlama 7B Python is a large language model with 7B parameters developed by Meta, focusing on Python code generation. It provides a quantized version in the GGUF format.