Instructions to use ATH-MaaS/Ovis1.6-Gemma2-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ATH-MaaS/Ovis1.6-Gemma2-9B with Transformers:

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

pipe = pipeline("image-text-to-text", model="ATH-MaaS/Ovis1.6-Gemma2-9B", 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/Ovis1.6-Gemma2-9B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ATH-MaaS/Ovis1.6-Gemma2-9B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ATH-MaaS/Ovis1.6-Gemma2-9B"
# 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/Ovis1.6-Gemma2-9B",
		"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/Ovis1.6-Gemma2-9B

SGLang

How to use ATH-MaaS/Ovis1.6-Gemma2-9B 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/Ovis1.6-Gemma2-9B" \
    --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/Ovis1.6-Gemma2-9B",
		"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/Ovis1.6-Gemma2-9B" \
        --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/Ovis1.6-Gemma2-9B",
		"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/Ovis1.6-Gemma2-9B with Docker Model Runner:
```
docker model run hf.co/ATH-MaaS/Ovis1.6-Gemma2-9B
```

xxyyy123 commited on Oct 22, 2024

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@@ -31,6 +31,8 @@ Built upon Ovis1.5, **Ovis1.6** further enhances high-resolution image processin
 | Ovis MLLMs        | ViT         | LLM                |                          Model Weights                          | Demo                                                             |
 |:------------------|:-----------:|:------------------:|:---------------------------------------------------------------:|:----------------------------------------------------------------:|
 | Ovis1.6-Gemma2-9B | Siglip-400M | Gemma2-9B-It       | [Huggingface](https://huggingface.co/AIDC-AI/Ovis1.6-Gemma2-9B) | [Space](https://huggingface.co/spaces/AIDC-AI/Ovis1.6-Gemma2-9B) |
 ## Performance
 With just **10B** parameters, **Ovis1.6-Gemma2-9B** leads the [OpenCompass](https://github.com/open-compass/VLMEvalKit) benchmark among open-source MLLMs within **30B** parameters.

 | Ovis MLLMs        | ViT         | LLM                |                          Model Weights                          | Demo                                                             |
 |:------------------|:-----------:|:------------------:|:---------------------------------------------------------------:|:----------------------------------------------------------------:|
 | Ovis1.6-Gemma2-9B | Siglip-400M | Gemma2-9B-It       | [Huggingface](https://huggingface.co/AIDC-AI/Ovis1.6-Gemma2-9B) | [Space](https://huggingface.co/spaces/AIDC-AI/Ovis1.6-Gemma2-9B) |
+| Ovis1.6-Llama3.2-3B | Siglip-400M | Llama-3.2-3B-Instruct       | [Huggingface](https://huggingface.co/AIDC-AI/Ovis1.6-Llama3.2-3B) | [Space](https://huggingface.co/spaces/AIDC-AI/Ovis1.6-Llama3.2-3B) |
 ## Performance
 With just **10B** parameters, **Ovis1.6-Gemma2-9B** leads the [OpenCompass](https://github.com/open-compass/VLMEvalKit) benchmark among open-source MLLMs within **30B** parameters.