Instructions to use bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF",
	filename="mistralai_Mistral-Medium-3.5-128B-IQ1_M.gguf",
)

llm.create_chat_completion(
	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"
					}
				}
			]
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF: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 bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF: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 bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bartowski/mistralai_Mistral-Medium-3.5-128B-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": "bartowski/mistralai_Mistral-Medium-3.5-128B-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/bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M

Ollama
How to use bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF with Ollama:
```
ollama run hf.co/bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M
```

Unsloth Studio new

How to use bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF 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 bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF 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 bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF to start chatting

Pi new

How to use bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF with Docker Model Runner:
```
docker model run hf.co/bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M
```

Lemonade

How to use bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull bartowski/mistralai_Mistral-Medium-3.5-128B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.mistralai_Mistral-Medium-3.5-128B-GGUF-Q4_K_M

List all available models

lemonade list

Do these quants suffer the same issue as the Unsloth quants?

by JJ404GO - opened 27 days ago

Discussion

JJ404GO

27 days ago

Do these quants suffer the same issue as the Unsloth quants?

https://huggingface.co/unsloth/Mistral-Medium-3.5-128B-GGUF

"We’re working with Mistral on llama.cpp GGUF implementation. Testing shows that this behavior occurs regardless of who or how the model was converted GGUF. The model initially responds correctly, but over long context, does not work properly.
Mistral has now labeled GGUF support as a WIP (work in progress). The issue appears most likely to be with the current GGUF parser. Will update once resolved."

Rotating

26 days ago

I'm assuming so. It's interesting that there's nothing about it on the llama.cpp github as far as I can tell.

danielhanchen

25 days ago

We worked with Mistral and fixed our GGUFs - it was sadly a nasty YaRN parsing error which propagated to llama.cpp and transformers - see https://huggingface.co/mistralai/Mistral-Medium-3.5-128B/discussions/18

bartowski

Owner 24 days ago

hey sorry I've been out of commission for a few days, will be fixing this today

bartowski changed discussion status to closed 24 days ago

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