How to use from
SGLang
Install from pip and serve model
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "prithivMLmods/Herculis-CUA-GUI-Actioner-4B-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prithivMLmods/Herculis-CUA-GUI-Actioner-4B-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 images
docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "prithivMLmods/Herculis-CUA-GUI-Actioner-4B-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "prithivMLmods/Herculis-CUA-GUI-Actioner-4B-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"
						}
					}
				]
			}
		]
	}'
Quick Links

Herculis-CUA-GUI-Actioner-4B-GGUF

Herculis-CUA-GUI-Actioner-4B is a Computer Use Agent (CUA) multimodal model designed for GUI understanding, UI localization, and action execution across web, desktop, and mobile environments. It focuses on visual grounding, intent driven actioning, and UI based question answering (VQA), enabling reliable interaction with real world software interfaces. The model is optimized for efficient inference while maintaining strong accuracy on complex UI workflows.

Quick Start with llama.cpp

Link: https://huggingface.co/prithivMLmods/Herculis-CUA-GUI-Actioner-4B-GGUF?library=llama-cpp-python

Herculis-CUA-GUI-Actioner-4B [GGUF]

File Name Quant Type File Size File Link
Herculis-CUA-GUI-Actioner-4B.BF16.gguf BF16 6.18 GB Download
Herculis-CUA-GUI-Actioner-4B.F16.gguf F16 6.18 GB Download
Herculis-CUA-GUI-Actioner-4B.F32.gguf F32 12.3 GB Download
Herculis-CUA-GUI-Actioner-4B.Q8_0.gguf Q8_0 3.29 GB Download
Herculis-CUA-GUI-Actioner-4B.mmproj-bf16.gguf mmproj-bf16 1.34 GB Download
Herculis-CUA-GUI-Actioner-4B.mmproj-f16.gguf mmproj-f16 1.34 GB Download
Herculis-CUA-GUI-Actioner-4B.mmproj-f32.gguf mmproj-f32 2.67 GB Download
Herculis-CUA-GUI-Actioner-4B.mmproj-q8_0.gguf mmproj-q8_0 848 MB Download

Quants Usage

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png

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172
GGUF
Model size
3B params
Architecture
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