Instructions to use ATH-MaaS/Ovis2-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ATH-MaaS/Ovis2-8B with Transformers:

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

pipe = pipeline("image-text-to-text", model="ATH-MaaS/Ovis2-8B", 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 AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("ATH-MaaS/Ovis2-8B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ATH-MaaS/Ovis2-8B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ATH-MaaS/Ovis2-8B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ATH-MaaS/Ovis2-8B",
		"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/ATH-MaaS/Ovis2-8B

SGLang

How to use ATH-MaaS/Ovis2-8B 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 "ATH-MaaS/Ovis2-8B" \
    --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": "ATH-MaaS/Ovis2-8B",
		"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 "ATH-MaaS/Ovis2-8B" \
        --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": "ATH-MaaS/Ovis2-8B",
		"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 ATH-MaaS/Ovis2-8B with Docker Model Runner:
```
docker model run hf.co/ATH-MaaS/Ovis2-8B
```

runninglsy commited on Feb 19, 2025

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@@ -69,6 +69,13 @@ We are pleased to announce the release of **Ovis2**, our latest advancement in m
 | MTVQA                        | 28.5            | 27.2                 | 23.1            |         19.2 |                 28   | 29.4       | **29.7**   |
 ### Video Benchmark
 ### Reasoning Benchmark
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/658a8a837959448ef5500ce5/aGc1DZLPEeERd0jGW9JRA.png)

 | MTVQA                        | 28.5            | 27.2                 | 23.1            |         19.2 |                 28   | 29.4       | **29.7**   |
 ### Video Benchmark
+|  Benchmark          | Qwen2.5-VL-7B | InternVL2.5-8B | LLaVA-OV-7B        | InternVL2.5-4B | Ovis2-4B  | Ovis2-8B      |
+|:--------------------|:-------------:|:--------------:|:------------------:|:--------------:|:---------:|:-------------:|
+| VideoMME(wo/w-subs) | 65.1/71.6     | 64.2 / 66.9    | 58.2/61.5          | 62.3 / 63.6    | 64.0/66.3 | **68.0/71.6** |
+| MVBench             | 69.6          | **72.0**       | 56.7               | 71.6           | 68.45     | 68.15         |
+| MLVU(M-Avg/G-Avg)   | 70.2/-        | 68.9/-         | 64.7/-             | 68.3/-         | 70.8/4.23 | **76.4**/4.25 |
+| MMBench-Video       | 1.79          | 1.68           | -                  | 1.73           | 1.69      | **1.85**      |
+| TempCompass         | **71.7**      | -              | -                  | -              | 67.02     | 69.28         |
 ### Reasoning Benchmark
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/658a8a837959448ef5500ce5/aGc1DZLPEeERd0jGW9JRA.png)