You can deploy this model and start earning money today!

tensorblock/
K2S3-Mistral-7bx2-48layers_v1.2-GGUF

Name: K2S3-Mistral-7bx2-48layers_v1.2-GGUF
Rating: 2.5 (15 reviews)

Changgil/K2S3-Mistral-7bx2-48layers_v1.2

Views

No views yet

Website

Discord

GitHub

Changgil/K2S3-Mistral-7bx2-48layers_v1.2 - GGUF

This repo contains GGUF format model files for Changgil/K2S3-Mistral-7bx2-48layers_v1.2.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.

Our projects

Forge
Forge Project
An OpenAI-compatible multi-provider routing layer.
🚀 Try it now! 🚀
Awesome MCP Servers	TensorBlock Studio
MCP Servers	Studio
A comprehensive collection of Model Context Protocol (MCP) servers.	A lightweight, open, and extensible multi-LLM interaction studio.
👀 See what we built 👀	👀 See what we built 👀

## Prompt template

Model file specification

Filename	Quant type	File Size	Description
K2S3-Mistral-7bx2-48layers_v1.2-Q2_K.gguf	Q2_K	3.799 GB	smallest, significant quality loss - not recommended for most purposes
K2S3-Mistral-7bx2-48layers_v1.2-Q3_K_S.gguf	Q3_K_S	4.421 GB	very small, high quality loss
K2S3-Mistral-7bx2-48layers_v1.2-Q3_K_M.gguf	Q3_K_M	4.916 GB	very small, high quality loss
K2S3-Mistral-7bx2-48layers_v1.2-Q3_K_L.gguf	Q3_K_L	5.339 GB	small, substantial quality loss
K2S3-Mistral-7bx2-48layers_v1.2-Q4_0.gguf	Q4_0	5.740 GB	legacy; small, very high quality loss - prefer using Q3_K_M
K2S3-Mistral-7bx2-48layers_v1.2-Q4_K_S.gguf	Q4_K_S	5.783 GB	small, greater quality loss
K2S3-Mistral-7bx2-48layers_v1.2-Q4_K_M.gguf	Q4_K_M	6.103 GB	medium, balanced quality - recommended
K2S3-Mistral-7bx2-48layers_v1.2-Q5_0.gguf	Q5_0	6.982 GB	legacy; medium, balanced quality - prefer using Q4_K_M
K2S3-Mistral-7bx2-48layers_v1.2-Q5_K_S.gguf	Q5_K_S	6.982 GB	large, low quality loss - recommended
K2S3-Mistral-7bx2-48layers_v1.2-Q5_K_M.gguf	Q5_K_M	7.169 GB	large, very low quality loss - recommended
K2S3-Mistral-7bx2-48layers_v1.2-Q6_K.gguf	Q6_K	8.301 GB	very large, extremely low quality loss
K2S3-Mistral-7bx2-48layers_v1.2-Q8_0.gguf	Q8_0	10.751 GB	very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/K2S3-Mistral-7bx2-48layers_v1.2-GGUF --include "K2S3-Mistral-7bx2-48layers_v1.2-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/K2S3-Mistral-7bx2-48layers_v1.2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'