Instructions to use OS-Copilot/OS-Atlas-Pro-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OS-Copilot/OS-Atlas-Pro-4B with Transformers:

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

pipe = pipeline("image-text-to-text", model="OS-Copilot/OS-Atlas-Pro-4B", trust_remote_code=True)
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 AutoModel
model = AutoModel.from_pretrained("OS-Copilot/OS-Atlas-Pro-4B", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use OS-Copilot/OS-Atlas-Pro-4B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OS-Copilot/OS-Atlas-Pro-4B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OS-Copilot/OS-Atlas-Pro-4B",
		"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/OS-Copilot/OS-Atlas-Pro-4B

SGLang

How to use OS-Copilot/OS-Atlas-Pro-4B 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 "OS-Copilot/OS-Atlas-Pro-4B" \
    --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": "OS-Copilot/OS-Atlas-Pro-4B",
		"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 "OS-Copilot/OS-Atlas-Pro-4B" \
        --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": "OS-Copilot/OS-Atlas-Pro-4B",
		"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 OS-Copilot/OS-Atlas-Pro-4B with Docker Model Runner:
```
docker model run hf.co/OS-Copilot/OS-Atlas-Pro-4B
```

numbmelon commited on Nov 19, 2024

Commit

7625c55

verified ·

1 Parent(s): a6dbe5f

Update README.md

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README.md +6 -3

README.md CHANGED Viewed

@@ -23,8 +23,8 @@ For GUI grounding tasks, you can use:
 - [OS-Atlas-Base-4B](https://huggingface.co/OS-Copilot/OS-Atlas-Base-4B)
 For generating single-step actions in GUI agent tasks, you can use:
-- [OS-Atlas-Action-7B](https://huggingface.co/OS-Copilot/OS-Atlas-Pro-7B)
-- [OS-Atlas-Action-4B](https://huggingface.co/OS-Copilot/OS-Atlas-Pro-4B)
 ## OS-Atlas-Action-4B
@@ -39,6 +39,9 @@ pip install transformers
 For additional dependencies, please refer to the [InternVL2 documentation](https://internvl.readthedocs.io/en/latest/get_started/installation.html)
 ### Example Inference Code
 ```python
 import torch
 import torchvision.transforms as T
@@ -123,7 +126,7 @@ def load_image(image_file, input_size=448, max_num=6):
     return pixel_values
 # If you want to load a model using multiple GPUs, please refer to the `Multiple GPUs` section.
-path = 'https://github.com/OS-Copilot/OS-Atlas/blob/main/exmaples/images/action_example_1.jpg'
 model = AutoModel.from_pretrained(
     path,
     torch_dtype=torch.bfloat16,

 - [OS-Atlas-Base-4B](https://huggingface.co/OS-Copilot/OS-Atlas-Base-4B)
 For generating single-step actions in GUI agent tasks, you can use:
+- [OS-Atlas-Pro-7B](https://huggingface.co/OS-Copilot/OS-Atlas-Pro-7B)
+- [OS-Atlas-Pro-4B](https://huggingface.co/OS-Copilot/OS-Atlas-Pro-4B)
 ## OS-Atlas-Action-4B
 For additional dependencies, please refer to the [InternVL2 documentation](https://internvl.readthedocs.io/en/latest/get_started/installation.html)
 ### Example Inference Code
+First download the [example image](https://github.com/OS-Copilot/OS-Atlas/blob/main/examples/images/action_example_1.jpg) and save it to the current directory.
+Inference code:
 ```python
 import torch
 import torchvision.transforms as T
     return pixel_values
 # If you want to load a model using multiple GPUs, please refer to the `Multiple GPUs` section.
+path = './action_example_1.jpg' # change to your example image path
 model = AutoModel.from_pretrained(
     path,
     torch_dtype=torch.bfloat16,