Instructions to use pierretokns/smolvlm-500m-ccmcp-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use pierretokns/smolvlm-500m-ccmcp-v1 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 pierretokns/smolvlm-500m-ccmcp-v1:F16
# Run inference directly in the terminal:
llama cli -hf pierretokns/smolvlm-500m-ccmcp-v1:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf pierretokns/smolvlm-500m-ccmcp-v1:F16
# Run inference directly in the terminal:
llama cli -hf pierretokns/smolvlm-500m-ccmcp-v1:F16

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 pierretokns/smolvlm-500m-ccmcp-v1:F16
# Run inference directly in the terminal:
./llama-cli -hf pierretokns/smolvlm-500m-ccmcp-v1:F16

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 pierretokns/smolvlm-500m-ccmcp-v1:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf pierretokns/smolvlm-500m-ccmcp-v1:F16

Use Docker

docker model run hf.co/pierretokns/smolvlm-500m-ccmcp-v1:F16

LM Studio
Jan

vLLM

How to use pierretokns/smolvlm-500m-ccmcp-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "pierretokns/smolvlm-500m-ccmcp-v1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "pierretokns/smolvlm-500m-ccmcp-v1",
		"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/pierretokns/smolvlm-500m-ccmcp-v1:F16

Ollama
How to use pierretokns/smolvlm-500m-ccmcp-v1 with Ollama:
```
ollama run hf.co/pierretokns/smolvlm-500m-ccmcp-v1:F16
```
Unsloth Desktop
Docker Model Runner
How to use pierretokns/smolvlm-500m-ccmcp-v1 with Docker Model Runner:
```
docker model run hf.co/pierretokns/smolvlm-500m-ccmcp-v1:F16
```

Lemonade

How to use pierretokns/smolvlm-500m-ccmcp-v1 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull pierretokns/smolvlm-500m-ccmcp-v1:F16

Run and chat with the model

lemonade run user.smolvlm-500m-ccmcp-v1-F16

List all available models

lemonade list

Atomic Chat

smolvlm-500m-ccmcp-v1

GUI grounding model trained on ScreenSpot dataset for Claude-compatible computer use.

Files

File	Description	Size
`mmproj-smolvlm-500m-ccmcp-v1-f16.gguf`	Vision projector (F16)	190.2 MB
`smolvlm-500m-ccmcp-v1-Q4_K_M.gguf`	Main model (Q4_K_M)	289.2 MB
`smolvlm-500m-ccmcp-v1-f16.gguf`	Main model (F16)	782.4 MB

Training

Base Model: HuggingFaceTB/SmolVLM-500M-Instruct
Dataset: ScreenSpot GUI grounding (1,017 examples)
Method: LoRA fine-tuning (r=16, alpha=32)
Task: Predict click coordinates in Claude format

Output Format

{"action": "left_click", "coordinate": [847, 523]}

Usage with Ollama

# Modelfile
FROM ./smolvlm-500m-ccmcp-v1-Q4_K_M.gguf
FROM ./mmproj-smolvlm-500m-ccmcp-v1-f16.gguf
PARAMETER num_ctx 4096
PARAMETER temperature 0.1
SYSTEM "You are a GUI grounding assistant. Given a screenshot and instruction, output click coordinates as JSON."

ollama create smolvlm_500m_ccmcp_v1 -f Modelfile
ollama run smolvlm_500m_ccmcp_v1 --image screenshot.png "Click the Submit button"

License

Apache 2.0 (inherits from base model)

Downloads last month: 54

GGUF

Model size

0.4B params

Architecture

llama

Hardware compatibility

4-bit

16-bit

Model tree for pierretokns/smolvlm-500m-ccmcp-v1

Base model

HuggingFaceTB/SmolLM2-360M

Quantized

HuggingFaceTB/SmolLM2-360M-Instruct

Quantized

HuggingFaceTB/SmolVLM-500M-Instruct

Quantized

(28)

this model