Instructions to use cortexso/mistral-small-24b 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/mistral-small-24b 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/mistral-small-24b:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf cortexso/mistral-small-24b:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf cortexso/mistral-small-24b:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf cortexso/mistral-small-24b:Q4_K_M

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/mistral-small-24b:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf cortexso/mistral-small-24b:Q4_K_M

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/mistral-small-24b:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf cortexso/mistral-small-24b:Q4_K_M

Use Docker

docker model run hf.co/cortexso/mistral-small-24b:Q4_K_M

LM Studio
Jan

vLLM

How to use cortexso/mistral-small-24b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cortexso/mistral-small-24b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cortexso/mistral-small-24b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/cortexso/mistral-small-24b:Q4_K_M

Ollama
How to use cortexso/mistral-small-24b with Ollama:
```
ollama run hf.co/cortexso/mistral-small-24b:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use cortexso/mistral-small-24b with Docker Model Runner:
```
docker model run hf.co/cortexso/mistral-small-24b:Q4_K_M
```

Lemonade

How to use cortexso/mistral-small-24b with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull cortexso/mistral-small-24b:Q4_K_M

Run and chat with the model

lemonade run user.mistral-small-24b-Q4_K_M

List all available models

lemonade list

Atomic Chat

mistral-small-24b / README.md

Minh141120

Update README.md

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	---
	license: mit
	pipeline_tag: text-generation
	tags:
	- cortex.cpp
	---
	## Overview
	The 'mistral-small-24b' model is an advanced AI language model optimized for a variety of natural language processing tasks. It is particularly well-suited for applications such as text generation, chatbots, content summarization, and language translation. Built on the foundation of 'mistralai/Mistral-Small-24B-Base-2501', it leverages state-of-the-art techniques for understanding and generating human-like text. Users can expect significant improvements in fluency and contextual relevance, making it effective for both professional and creative use cases. Its efficiency allows for deployment in resource-constrained environments, catering to a diverse range of industries and applications.
	## Variants
	\| No \| Variant \| Cortex CLI command \|
	\| --- \| --- \| --- \|
	\| 1 \| [Mistral-Small-24b](https://huggingface.co/cortexso/mistral-small-24b/tree/24b) \| cortex run mistral-small-24b:24b \|
	## Use it with Jan (UI)
	1. Install Jan using [Quickstart](https://jan.ai/docs/quickstart)
	2. Use in Jan model Hub:

	```bash
	cortexso/mistral-small-24b
	```

	## Use it with Cortex (CLI)
	1. Install Cortex using [Quickstart](https://cortex.jan.ai/docs/quickstart)
	2. Run the model with command:

	```bash
	cortex run mistral-small-24b
	```

	## Credits
	- Author: mistralai
	- Converter: [Homebrew](https://www.homebrew.ltd/)
	- Original License: [License](https://choosealicense.com/licenses/apache-2.0/)
	- Paper: [Mistral Small 3 Blog](https://mistral.ai/news/mistral-small-3)