Instructions to use ThomasBaruzier/Qwen2.5-72B-Instruct-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 ThomasBaruzier/Qwen2.5-72B-Instruct-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 ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ThomasBaruzier/Qwen2.5-72B-Instruct-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 ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf ThomasBaruzier/Qwen2.5-72B-Instruct-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 ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M

Use Docker

docker model run hf.co/ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ThomasBaruzier/Qwen2.5-72B-Instruct-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": "ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M

Ollama
How to use ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF with Ollama:
```
ollama run hf.co/ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M
```
Unsloth Desktop

How to use ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF with Docker Model Runner:
```
docker model run hf.co/ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M
```

Lemonade

How to use ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwen2.5-72B-Instruct-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ThomasBaruzier/Qwen2.5-72B-Instruct-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 ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "ThomasBaruzier/Qwen2.5-72B-Instruct-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

ThomasBaruzier commited on Sep 26, 2024

Commit

9ce8e86

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1 Parent(s): fa09447

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+Qwen2.5-72B-Instruct
+Quant	Size (MB)	PPL	Size (%)	Accuracy (%)	PPL error rate
+IQ1_S	21640	7.6552			0.10700
+IQ1_M	22641	7.2982			0.10210
+IQ2_XXS	24310	6.3958			0.08698
+IQ2_XS	25805	6.0909			0.08248
+IQ2_S	26645	6.0318			0.08180
+IQ2_M	27980	5.7589			0.07721
+Q2_K_S	28200	5.9731			0.08266
+Q2_K	28431	5.9188			0.08204
+IQ3_XXS	30370	5.5227			0.07426
+IQ3_XS	31321	5.4357			0.07228
+IQ3_S	32891	5.3782			0.07153
+Q3_K_S	32891	5.4492			0.07429
+IQ3_M	33859	5.3550			0.07069
+Q3_K_M	35953	5.4069			0.07356
+Q3_K_L	37676	5.4116			0.07371
+IQ4_XS	37870	5.2776			0.07108
+IQ4_NL	39402	5.2747			0.07099
+Q4_0	39467	5.2998			0.07117
+Q4_K_S	41857	5.2535			0.07066
+Q4_1	43581	5.2801			0.07092
+Q4_K_M	45220	5.2478			0.07054