solidrust/Average_Normie_v2_l3_8B-AWQ

jeiku/Average_Normie_v2_l3_8B AWQ

• Model creator: jeiku
• Original model: Average_Normie_v2_l3_8B

Model Summary

This is a merge of pre-trained language models created using mergekit.

This model was merged using the Model Stock merge method using ResplendentAI/Kei_Llama3_8B as a base.

The following models were included in the merge:

• ChaoticNeutrals/Poppy_Porpoise-v0.7-L3-8B
• vicgalle/Roleplay-Llama-3-8B
• cgato/L3-TheSpice-8b-v0.1.3

About AWQ

AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, it offers faster Transformers-based inference with equivalent or better quality compared to the most commonly used GPTQ settings.

AWQ models are currently supported on Linux and Windows, with NVidia GPUs only. macOS users: please use GGUF models instead.

It is supported by:

• Text Generation Webui - using Loader: AutoAWQ
• vLLM - version 0.2.2 or later for support for all model types.
• Hugging Face Text Generation Inference (TGI)
• Transformers version 4.35.0 and later, from any code or client that supports Transformers
• AutoAWQ - for use from Python code