Instructions to use openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-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 openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
llama cli -hf openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0

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 openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0

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 openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0

Use Docker

docker model run hf.co/openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0

LM Studio
Jan

vLLM

How to use openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0

Ollama
How to use openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF with Ollama:
```
ollama run hf.co/openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0
```
Unsloth Desktop
Docker Model Runner
How to use openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF with Docker Model Runner:
```
docker model run hf.co/openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0
```

Lemonade

How to use openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF:Q8_0

Run and chat with the model

lemonade run user.Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF-Q8_0

List all available models

lemonade list

Atomic Chat

Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF / README.md

openfree

Upload README.md with huggingface_hub

18b81b9 verified over 1 year ago

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	---
	base_model: mistralai/Mistral-Small-3.1-24B-Instruct-2503
	language:
	- en
	- fr
	- de
	- es
	- pt
	- it
	- ja
	- ko
	- ru
	- zh
	- ar
	- fa
	- id
	- ms
	- ne
	- pl
	- ro
	- sr
	- sv
	- tr
	- uk
	- vi
	- hi
	- bn
	library_name: vllm
	license: apache-2.0
	pipeline_tag: image-text-to-text
	tags:
	- llama-cpp
	- gguf-my-repo
	inference: false
	extra_gated_description: If you want to learn more about how we process your personal
	data, please read our <a href="https://mistral.ai/terms/">Privacy Policy</a>.
	---

	# openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF
	This model was converted to GGUF format from [`mistralai/Mistral-Small-3.1-24B-Instruct-2503`](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
	Refer to the [original model card](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503) for more details on the model.

	## Use with llama.cpp
	Install llama.cpp through brew (works on Mac and Linux)

	```bash
	brew install llama.cpp

	```
	Invoke the llama.cpp server or the CLI.

	### CLI:
	```bash
	llama-cli --hf-repo openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF --hf-file mistral-small-3.1-24b-instruct-2503-q8_0.gguf -p "The meaning to life and the universe is"
	```

	### Server:
	```bash
	llama-server --hf-repo openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF --hf-file mistral-small-3.1-24b-instruct-2503-q8_0.gguf -c 2048
	```

	Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

	Step 1: Clone llama.cpp from GitHub.
	```
	git clone https://github.com/ggerganov/llama.cpp
	```

	Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
	```
	cd llama.cpp && LLAMA_CURL=1 make
	```

	Step 3: Run inference through the main binary.
	```
	./llama-cli --hf-repo openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF --hf-file mistral-small-3.1-24b-instruct-2503-q8_0.gguf -p "The meaning to life and the universe is"
	```
	or
	```
	./llama-server --hf-repo openfree/Mistral-Small-3.1-24B-Instruct-2503-Q8_0-GGUF --hf-file mistral-small-3.1-24b-instruct-2503-q8_0.gguf -c 2048
	```