Instructions to use AXERA-TECH/Qwen2.5-VL-3B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AXERA-TECH/Qwen2.5-VL-3B-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-3B-Instruct")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("AXERA-TECH/Qwen2.5-VL-3B-Instruct", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AXERA-TECH/Qwen2.5-VL-3B-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-3B-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-3B-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/AXERA-TECH/Qwen2.5-VL-3B-Instruct

SGLang

How to use AXERA-TECH/Qwen2.5-VL-3B-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-3B-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-3B-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-3B-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-3B-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use AXERA-TECH/Qwen2.5-VL-3B-Instruct with Docker Model Runner:
```
docker model run hf.co/AXERA-TECH/Qwen2.5-VL-3B-Instruct
```

lihongjie commited on Dec 11, 2025

Commit

0f72562

1 Parent(s): bb880b5

优化tokenizer和 kv cache内存

Browse files

Files changed (4) hide show

main_ax650 +2 -2
qwen2.5_tokenizer.txt +0 -0
run_qwen2_5_vl_image.sh +1 -1
run_qwen2_5_vl_video.sh +1 -1

main_ax650 CHANGED Viewed

@@ -1,3 +1,3 @@
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-oid sha256:bdbd72d706b584081c103af2fe6a59426140f0ed0b79d9baf4282a601e2e014c
-size 6593472

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+oid sha256:9f6cfcf0021a15a3baea0513e0eb6b17bdfbe08928de0e74619e6684a13a1493
+size 6808392

qwen2.5_tokenizer.txt ADDED Viewed

The diff for this file is too large to render. See raw diff

run_qwen2_5_vl_image.sh CHANGED Viewed

@@ -7,7 +7,7 @@ AXMODEL_DIR=./Qwen2.5-VL-3B-Instruct-AX650-chunk_prefill_512
 --bos 0 --eos 0 \
 --dynamic_load_axmodel_layer 0 \
 --use_mmap_load_embed 1 \
---filename_tokenizer_model "http://127.0.0.1:12345" \
 --filename_post_axmodel "${AXMODEL_DIR}/qwen2_5_vl_post.axmodel" \
 --use_topk 0 \
 --filename_tokens_embed "${AXMODEL_DIR}/model.embed_tokens.weight.bfloat16.bin" \

 --bos 0 --eos 0 \
 --dynamic_load_axmodel_layer 0 \
 --use_mmap_load_embed 1 \
+--filename_tokenizer_model "qwen2.5_tokenizer.txt" \
 --filename_post_axmodel "${AXMODEL_DIR}/qwen2_5_vl_post.axmodel" \
 --use_topk 0 \
 --filename_tokens_embed "${AXMODEL_DIR}/model.embed_tokens.weight.bfloat16.bin" \

run_qwen2_5_vl_video.sh CHANGED Viewed

@@ -7,7 +7,7 @@ AXMODEL_DIR=./Qwen2.5-VL-3B-Instruct-AX650-chunk_prefill_512
 --bos 0 --eos 0 \
 --dynamic_load_axmodel_layer 0 \
 --use_mmap_load_embed 1 \
---filename_tokenizer_model "http://127.0.0.1:12345" \
 --filename_post_axmodel "${AXMODEL_DIR}/qwen2_5_vl_post.axmodel" \
 --use_topk 0 \
 --filename_tokens_embed "${AXMODEL_DIR}/model.embed_tokens.weight.bfloat16.bin" \

 --bos 0 --eos 0 \
 --dynamic_load_axmodel_layer 0 \
 --use_mmap_load_embed 1 \
+--filename_tokenizer_model "qwen2.5_tokenizer.txt" \
 --filename_post_axmodel "${AXMODEL_DIR}/qwen2_5_vl_post.axmodel" \
 --use_topk 0 \
 --filename_tokens_embed "${AXMODEL_DIR}/model.embed_tokens.weight.bfloat16.bin" \