Instructions to use shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_S

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_S

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_S
# Run inference directly in the terminal:
./llama-cli -hf shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_S

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_S
# Run inference directly in the terminal:
./build/bin/llama-cli -hf shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_S

Use Docker

docker model run hf.co/shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_S

LM Studio
Jan
Ollama
How to use shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF with Ollama:
```
ollama run hf.co/shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_S
```
Unsloth Desktop
Docker Model Runner
How to use shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF with Docker Model Runner:
```
docker model run hf.co/shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_S
```

Lemonade

How to use shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull shenberg1/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_S

Run and chat with the model

lemonade run user.Mixtral-8x7B-Instruct-v0.1-GGUF-Q4_K_S

List all available models

lemonade list

Atomic Chat

Description

This repo contains GGUF format model files for Mistral AI_'s Mixtral 8X7B Instruct v0.1.

The f16 model (as well as several other formats) are well over the 50GB limit so there are a few missing.

This is for personal use, but if you use or would like to use it please let me know! And I'll be happy to dedicate more time to making more GGUF model files available to people :)

Downloads last month: 60

GGUF

Model size

47B params

Architecture

llama

Hardware compatibility

4-bit

8-bit

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