Instructions to use mobileforge-anonymous/ForgeOwl-8B-200tasks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mobileforge-anonymous/ForgeOwl-8B-200tasks with Transformers:

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

pipe = pipeline("image-text-to-text", model="mobileforge-anonymous/ForgeOwl-8B-200tasks")
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, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("mobileforge-anonymous/ForgeOwl-8B-200tasks")
model = AutoModelForMultimodalLM.from_pretrained("mobileforge-anonymous/ForgeOwl-8B-200tasks", device_map="auto")
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 Settings

vLLM

How to use mobileforge-anonymous/ForgeOwl-8B-200tasks with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mobileforge-anonymous/ForgeOwl-8B-200tasks"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mobileforge-anonymous/ForgeOwl-8B-200tasks",
		"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/mobileforge-anonymous/ForgeOwl-8B-200tasks

SGLang

How to use mobileforge-anonymous/ForgeOwl-8B-200tasks 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 "mobileforge-anonymous/ForgeOwl-8B-200tasks" \
    --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": "mobileforge-anonymous/ForgeOwl-8B-200tasks",
		"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 "mobileforge-anonymous/ForgeOwl-8B-200tasks" \
        --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": "mobileforge-anonymous/ForgeOwl-8B-200tasks",
		"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 mobileforge-anonymous/ForgeOwl-8B-200tasks with Docker Model Runner:
```
docker model run hf.co/mobileforge-anonymous/ForgeOwl-8B-200tasks
```

ForgeOwl-8B-200tasks / README.md

mobileforge-anonymous

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	---
	license: mit
	base_model: mPLUG/GUI-Owl-1.5-8B-Instruct
	library_name: transformers
	pipeline_tag: image-text-to-text
	tags:
	- mobile-gui
	- vision-language-model
	- anonymous-submission
	---

	# ForgeOwl-8B-200tasks

	ForgeOwl-8B-200tasks is the GUI-Owl-1.5-8B-Instruct policy adapted with MobileForge on `200` automatically generated target-app tasks. MobileForge uses the policy's own rollouts, hierarchical critic feedback, corrective hints, and hint-contextualized step-level GRPO. No human-written adaptation tasks, demonstrations, or reward labels are used.

	This repository is part of an anonymous ICLR submission artifact. Author and paper-identifying metadata will be added after review.

	Anonymous project page: https://mobileforge-anonymous.github.io/

	## Evaluation

	On AndroidWorld (`116` tasks), this checkpoint obtains `75/116` (`64.7%`) Pass@1, `85/116` (`73.3%`) Pass@2, and `86/116` (`74.1%`) Pass@3.

	Reproduction code and raw evaluation archives are available from the [anonymous code repository](https://github.com/mobileforge-anonymous/MobileForge) and [benchmark-results dataset](https://huggingface.co/datasets/mobileforge-anonymous/mobileforge-benchmark-results).

	## Usage and limitations

	Use the loading and prompting interface of [`mPLUG/GUI-Owl-1.5-8B-Instruct`](https://huggingface.co/mPLUG/GUI-Owl-1.5-8B-Instruct). The model can make incorrect or unsafe GUI actions; run it only in isolated test environments and inspect actions before using it with personal data.