Instructions to use cortexso/mixtral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use cortexso/mixtral 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 cortexso/mixtral
# Run inference directly in the terminal:
llama cli -hf cortexso/mixtral

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf cortexso/mixtral
# Run inference directly in the terminal:
llama cli -hf cortexso/mixtral

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 cortexso/mixtral
# Run inference directly in the terminal:
./llama-cli -hf cortexso/mixtral

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 cortexso/mixtral
# Run inference directly in the terminal:
./build/bin/llama-cli -hf cortexso/mixtral

Use Docker

docker model run hf.co/cortexso/mixtral

LM Studio
Jan
Ollama
How to use cortexso/mixtral with Ollama:
```
ollama run hf.co/cortexso/mixtral
```

Unsloth Studio

How to use cortexso/mixtral with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for cortexso/mixtral to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for cortexso/mixtral to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for cortexso/mixtral to start chatting

Atomic Chat new
Docker Model Runner
How to use cortexso/mixtral with Docker Model Runner:
```
docker model run hf.co/cortexso/mixtral
```

Lemonade

How to use cortexso/mixtral with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull cortexso/mixtral

Run and chat with the model

lemonade run user.mixtral-{{QUANT_TAG}}

List all available models

lemonade list

mixtral / README.md

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Update README.md

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	---
	license: apache-2.0
	---

	## Overview

	The Mixtral-7x8B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mistral-7x8Boutperforms Llama 2 70B on most benchmarks we tested.

	## Variants

	\| No \| Variant \| Cortex CLI command \|
	\| --- \| --- \| --- \|
	\| 1 \| [7x8b-gguf](https://huggingface.co/cortexhub/mixtral/tree/7x8b-gguf) \| `cortex run mixtral:7x8b-gguf` \|

	## Use it with Jan (UI)

	1. Install Jan using [Quickstart](https://jan.ai/docs/quickstart)
	2. Use in Jan model Hub:
	```
	cortexhub/mixtral
	```

	## Use it with Cortex (CLI)

	1. Install Cortex using [Quickstart](https://cortex.jan.ai/docs/quickstart)
	2. Run the model with command:
	```
	cortex run mixtral
	```

	## Credits

	- Author: Mistralai
	- Converter: [Homebrew](https://www.homebrew.ltd/)