Instructions to use Fintor/Fintor-GUI-S2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Fintor/Fintor-GUI-S2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="Fintor/Fintor-GUI-S2")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("Fintor/Fintor-GUI-S2")
model = AutoModelForImageTextToText.from_pretrained("Fintor/Fintor-GUI-S2")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Fintor/Fintor-GUI-S2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Fintor/Fintor-GUI-S2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Fintor/Fintor-GUI-S2",
		"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/Fintor/Fintor-GUI-S2

SGLang

How to use Fintor/Fintor-GUI-S2 with 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 "Fintor/Fintor-GUI-S2" \
    --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": "Fintor/Fintor-GUI-S2",
		"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 "Fintor/Fintor-GUI-S2" \
        --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": "Fintor/Fintor-GUI-S2",
		"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"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use Fintor/Fintor-GUI-S2 with Docker Model Runner:
```
docker model run hf.co/Fintor/Fintor-GUI-S2
```

MasoudJB commited on Apr 24, 2025

Commit

82b48fd

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Update README.md

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@@ -16,9 +16,8 @@ tags:
 ## Model Description
-Ui-Tars-7B-Instruct-Finetuned-Os-Atlas is a GUI grounding model finetuned from [**UI-TARS-7B-DPO**](https://huggingface.co/bytedance-research/UI-TARS-7B-DPO).
-This model used the OS-Copilot dataset for fine-tuning: [OS-Copilot](https://huggingface.co/datasets/OS-Copilot/OS-Atlas-data/tree/main).
 ## Evaluation Results
@@ -36,6 +35,8 @@ We also include evaluation scripts used on these benchmarks. The table below com
 ## Training procedure
 [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/am_fintor-neuralleap/huggingface/runs/hl90xquy?nw=nwuseram_fintor)
 This model was trained with SFT and LoRA.

 ## Model Description
+Fintor-GUI-S2 s is a GUI grounding model finetuned from [**UI-TARS-7B-DPO**](https://huggingface.co/bytedance-research/UI-TARS-7B-DPO).
 ## Evaluation Results
 ## Training procedure
+This model used the OS-Copilot dataset for fine-tuning: [OS-Copilot](https://huggingface.co/datasets/OS-Copilot/OS-Atlas-data/tree/main).
 [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/am_fintor-neuralleap/huggingface/runs/hl90xquy?nw=nwuseram_fintor)
 This model was trained with SFT and LoRA.