Instructions to use AXERA-TECH/Qwen2.5-VL-7B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AXERA-TECH/Qwen2.5-VL-7B-Instruct with Transformers:

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

pipe = pipeline("image-text-to-text", model="AXERA-TECH/Qwen2.5-VL-7B-Instruct")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("AXERA-TECH/Qwen2.5-VL-7B-Instruct", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AXERA-TECH/Qwen2.5-VL-7B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AXERA-TECH/Qwen2.5-VL-7B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AXERA-TECH/Qwen2.5-VL-7B-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/AXERA-TECH/Qwen2.5-VL-7B-Instruct

SGLang

How to use AXERA-TECH/Qwen2.5-VL-7B-Instruct 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 "AXERA-TECH/Qwen2.5-VL-7B-Instruct" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AXERA-TECH/Qwen2.5-VL-7B-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "AXERA-TECH/Qwen2.5-VL-7B-Instruct" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AXERA-TECH/Qwen2.5-VL-7B-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use AXERA-TECH/Qwen2.5-VL-7B-Instruct with Docker Model Runner:
```
docker model run hf.co/AXERA-TECH/Qwen2.5-VL-7B-Instruct
```

Qwen2.5-VL-7B-Instruct

Commit History

Update README.md

d6ded77
verified

qqc1989 commited on Aug 23, 2025

添加 main_ax650

4baace6

lihongjie commited on Aug 6, 2025

添加ax650版本

74e23e4

lihongjie commited on Aug 6, 2025

rename main_axcl to main_axcl_x86

d76d553

lihongjie commited on Aug 4, 2025

Update README.md

4cb4277
verified

qqc1989 commited on Aug 4, 2025

Upload config.json

ec9b3c8
verified

qqc1989 commited on Aug 2, 2025

update

955ad30

lihongjie commited on Aug 1, 2025

添加视频理解

ea06959

lihongjie commited on Aug 1, 2025

merge maste

dda8dc3

lihongjie commited on Aug 1, 2025

first commit

b149fbf

lihongjie commited on Jul 31, 2025

initial commit

ef27c77
verified

lihongjie007 commited on Jul 31, 2025

Commit History

Update README.md d6ded77 verified

添加 main_ax650 4baace6

添加ax650版本 74e23e4

rename main_axcl to main_axcl_x86 d76d553

Update README.md 4cb4277 verified

Upload config.json ec9b3c8 verified

update 955ad30

添加视频理解 ea06959

merge maste dda8dc3

first commit b149fbf

initial commit ef27c77 verified

Update README.md

d6ded77
verified

添加 main_ax650

4baace6

添加ax650版本

74e23e4

rename main_axcl to main_axcl_x86

d76d553

Update README.md

4cb4277
verified

Upload config.json

ec9b3c8
verified

update

955ad30

添加视频理解

ea06959

merge maste

dda8dc3

first commit

b149fbf

initial commit

ef27c77
verified