Instructions to use qihoo360/Inner-Adaptor-Architecture with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use qihoo360/Inner-Adaptor-Architecture with Transformers:

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

pipe = pipeline("image-text-to-text", model="qihoo360/Inner-Adaptor-Architecture", 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("qihoo360/Inner-Adaptor-Architecture", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use qihoo360/Inner-Adaptor-Architecture with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "qihoo360/Inner-Adaptor-Architecture"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "qihoo360/Inner-Adaptor-Architecture",
		"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/qihoo360/Inner-Adaptor-Architecture

SGLang

How to use qihoo360/Inner-Adaptor-Architecture 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 "qihoo360/Inner-Adaptor-Architecture" \
    --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": "qihoo360/Inner-Adaptor-Architecture",
		"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 "qihoo360/Inner-Adaptor-Architecture" \
        --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": "qihoo360/Inner-Adaptor-Architecture",
		"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 qihoo360/Inner-Adaptor-Architecture with Docker Model Runner:
```
docker model run hf.co/qihoo360/Inner-Adaptor-Architecture
```

Update pipeline tag and add library name

by nielsr HF Staff - opened Apr 16, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

+42

-12

Files changed (1) hide show

README.md +42 -12

README.md CHANGED Viewed

@@ -1,5 +1,4 @@
 ---
-license: apache-2.0
 datasets:
 - liuhaotian/LLaVA-CC3M-Pretrain-595K
 - liuhaotian/LLaVA-Instruct-150K
@@ -8,7 +7,9 @@ datasets:
 language:
 - zh
 - en
-pipeline_tag: visual-question-answering
 ---
 # Model Card for IAA: Inner-Adaptor Architecture
@@ -152,6 +153,42 @@ outputs = outputs.strip()
 print(outputs)
 ```
 ## We Are Hiring
 We are seeking academic interns in the Multimodal field. If interested, please send your resume to xiechunyu@360.cn.
@@ -168,19 +205,12 @@ If you find IAA useful for your research and applications, please cite using thi
 ```
 ## License
-This project utilizes certain datasets and checkpoints that are subject to their respective original licenses. Users must comply with all terms and conditions of these original licenses.
-The content of this project itself is licensed under the [Apache license 2.0]
-**Where to send questions or comments about the model:**
-https://github.com/360CVGroup/Inner-Adaptor-Architecture
 ## Related Projects
 This work wouldn't be possible without the incredible open-source code of these projects. Huge thanks!
 - [Meta Llama 3](https://github.com/meta-llama/llama3)
 - [LLaVA: Large Language and Vision Assistant](https://github.com/haotian-liu/LLaVA)
-- [360VL](https://github.com/360CVGroup/360VL)

 ---
 datasets:
 - liuhaotian/LLaVA-CC3M-Pretrain-595K
 - liuhaotian/LLaVA-Instruct-150K
 language:
 - zh
 - en
+license: apache-2.0
+pipeline_tag: image-text-to-text
+library_name: transformers
 ---
 # Model Card for IAA: Inner-Adaptor Architecture
 print(outputs)
 ```
+## CLI Inference
+Chat about images using IAA without the need of Gradio interface.
+```Shell
+name="qihoo360/Inner-Adaptor-Architecture"
+python -m iaa.eval.infer \
+    --model-path $name \
+    --image-path testimg/readpanda.jpg \
+    --task_type MM \
+```
+```Shell
+name="qihoo360/Inner-Adaptor-Architecture"
+python -m iaa.eval.infer_interleave \
+    --model-path $name \
+    --image-path testimg/COCO_train2014_000000014502.jpg \
+```
+## Evaluation
+First, download the MME image from the following link to ./MME/MME_Benchmark_release_version.
+https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models/tree/Evaluation
+```Shell
+bash scripts/mme.sh
+```
+For Refcoco testing, please refer to the following links for data downloads
+https://github.com/lichengunc/refer
+```Shell
+bash scripts/refcoco.sh
+```
+<!-- ## Acknowledgement -->
 ## We Are Hiring
 We are seeking academic interns in the Multimodal field. If interested, please send your resume to xiechunyu@360.cn.
 ```
 ## License
+This project utilizes certain datasets and checkpoints that are subject to their respective original licenses. Users must comply with all terms and conditions of these original licenses.
+The content of this project itself is licensed under the [Apache license 2.0](./LICENSE).
 ## Related Projects
 This work wouldn't be possible without the incredible open-source code of these projects. Huge thanks!
 - [Meta Llama 3](https://github.com/meta-llama/llama3)
 - [LLaVA: Large Language and Vision Assistant](https://github.com/haotian-liu/LLaVA)
+- [360VL](https://github.com/360CVGroup/360VL)