Quantization made by Richard Erkhov.

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llama-3-merged-linear - GGUF

• Model creator: https://huggingface.co/uygarkurt/
• Original model: https://huggingface.co/uygarkurt/llama-3-merged-linear/

Name	Quant method	Size
llama-3-merged-linear.Q2_K.gguf	Q2_K	2.96GB
llama-3-merged-linear.IQ3_XS.gguf	IQ3_XS	3.28GB
llama-3-merged-linear.IQ3_S.gguf	IQ3_S	3.43GB
llama-3-merged-linear.Q3_K_S.gguf	Q3_K_S	3.41GB
llama-3-merged-linear.IQ3_M.gguf	IQ3_M	3.52GB
llama-3-merged-linear.Q3_K.gguf	Q3_K	3.74GB
llama-3-merged-linear.Q3_K_M.gguf	Q3_K_M	3.74GB
llama-3-merged-linear.Q3_K_L.gguf	Q3_K_L	4.03GB
llama-3-merged-linear.IQ4_XS.gguf	IQ4_XS	4.18GB
llama-3-merged-linear.Q4_0.gguf	Q4_0	4.34GB
llama-3-merged-linear.IQ4_NL.gguf	IQ4_NL	4.38GB
llama-3-merged-linear.Q4_K_S.gguf	Q4_K_S	4.37GB
llama-3-merged-linear.Q4_K.gguf	Q4_K	4.58GB
llama-3-merged-linear.Q4_K_M.gguf	Q4_K_M	4.58GB
llama-3-merged-linear.Q4_1.gguf	Q4_1	4.78GB
llama-3-merged-linear.Q5_0.gguf	Q5_0	5.21GB
llama-3-merged-linear.Q5_K_S.gguf	Q5_K_S	5.21GB
llama-3-merged-linear.Q5_K.gguf	Q5_K	5.34GB
llama-3-merged-linear.Q5_K_M.gguf	Q5_K_M	5.34GB
llama-3-merged-linear.Q5_1.gguf	Q5_1	5.65GB
llama-3-merged-linear.Q6_K.gguf	Q6_K	6.14GB
llama-3-merged-linear.Q8_0.gguf	Q8_0	7.95GB

Original model description:

library_name: transformers license: mit

LLM Model Merging

YouTube Tutorial

Model Merging: Merge LLMs to Create Frankestein Models - Python, HuggingFace, Mergekit

GitHub

You can find the GitHub from here; https://github.com/uygarkurt/Model-Merge

In this specific case, I typed llama-3 into the open LLM leaderboard, took the best 3 models, merged them and created a better ranking model wihtout any training.

As the main libraries we will be using mergekit.