Instructions to use tencent/Hunyuan-A13B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tencent/Hunyuan-A13B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="tencent/Hunyuan-A13B-Instruct", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("tencent/Hunyuan-A13B-Instruct", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("tencent/Hunyuan-A13B-Instruct", trust_remote_code=True, device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use tencent/Hunyuan-A13B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tencent/Hunyuan-A13B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tencent/Hunyuan-A13B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/tencent/Hunyuan-A13B-Instruct

SGLang

How to use tencent/Hunyuan-A13B-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 "tencent/Hunyuan-A13B-Instruct" \
    --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": "tencent/Hunyuan-A13B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "tencent/Hunyuan-A13B-Instruct" \
        --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": "tencent/Hunyuan-A13B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use tencent/Hunyuan-A13B-Instruct with Docker Model Runner:
```
docker model run hf.co/tencent/Hunyuan-A13B-Instruct
```

asherszhang commited on Jun 30, 2025

Commit

f3ef13f

1 Parent(s): 96a5535

add vllm lastest image doc.

Browse files

Files changed (2) hide show

README.md +3 -7
README_CN.md +4 -8

README.md CHANGED Viewed

@@ -227,9 +227,7 @@ We provide a pre-built Docker image containing vLLM 0.8.5 with full support for
 - To get started:
 ```
-docker pull docker.cnb.cool/tencent/hunyuan/hunyuan-a13b:hunyuan-moe-A13B-vllm
-or
-docker pull hunyuaninfer/hunyuan-a13b:hunyuan-moe-A13B-vllm
 ```
 - Download Model file:
@@ -247,8 +245,7 @@ docker run --rm  --ipc=host \
         --net=host \
         --gpus=all \
         -it \
-        -e VLLM_USE_V1=0 \
-        --entrypoint python hunyuaninfer/hunyuan-a13b:hunyuan-moe-A13B-vllm \
         -m vllm.entrypoints.openai.api_server \
         --host 0.0.0.0 \
         --tensor-parallel-size 4 \
@@ -265,8 +262,7 @@ docker run --rm  --ipc=host \
         --net=host \
         --gpus=all \
         -it \
-        -e VLLM_USE_V1=0 \
-        --entrypoint python hunyuaninfer/hunyuan-a13b:hunyuan-moe-A13B-vllm \
         -m vllm.entrypoints.openai.api_server \
         --host 0.0.0.0 \
         --tensor-parallel-size 4 \

 - To get started:
 ```
+docker pull hunyuaninfer/hunyuan-infer-vllm-cuda12.4:v1
 ```
 - Download Model file:
         --net=host \
         --gpus=all \
         -it \
+        --entrypoint python3 hunyuaninfer/hunyuan-infer-vllm-cuda12.4:v1 \
         -m vllm.entrypoints.openai.api_server \
         --host 0.0.0.0 \
         --tensor-parallel-size 4 \
         --net=host \
         --gpus=all \
         -it \
+        --entrypoint python3 hunyuaninfer/hunyuan-infer-vllm-cuda12.4:v1 \
         -m vllm.entrypoints.openai.api_server \
         --host 0.0.0.0 \
         --tensor-parallel-size 4 \

README_CN.md CHANGED Viewed

@@ -180,14 +180,12 @@ print(response)
 ### Docker 镜像
-我们提供了一个预构建的 Docker 镜像，其中包含了支持本模型的 vLLM 0.8.5。当前官方 vLLM 正在持续开发中。**注意：该镜像要求使用 CUDA 12.8 版本。**
 - 快速开始方式如下：
 ```
-docker pull docker.cnb.cool/tencent/hunyuan/hunyuan-a13b:hunyuan-moe-A13B-vllm
-或
-docker pull hunyuaninfer/hunyuan-a13b:hunyuan-moe-A13B-vllm
 ```
 - 下载模型文件：
@@ -203,8 +201,7 @@ docker run --rm  --ipc=host \
         --net=host \
         --gpus=all \
         -it \
-        -e VLLM_USE_V1=0 \
-        --entrypoint python hunyuaninfer/hunyuan-a13b:hunyuan-moe-A13B-vllm \
         -m vllm.entrypoints.openai.api_server \
         --host 0.0.0.0 \
         --tensor-parallel-size 4 \
@@ -222,8 +219,7 @@ docker run --rm  --ipc=host \
         --net=host \
         --gpus=all \
         -it \
-        -e VLLM_USE_V1=0 \
-        --entrypoint python hunyuaninfer/hunyuan-a13b:hunyuan-moe-A13B-vllm \
         -m vllm.entrypoints.openai.api_server \
         --host 0.0.0.0 \
         --tensor-parallel-size 4 \

 ### Docker 镜像
+我们提供了一个基于官方 vLLM 0.8.5 版本的 Docker 镜像方便快速部署和测试。**注意：该镜像要求使用 CUDA 12.4 版本。**
 - 快速开始方式如下：
 ```
+docker pull hunyuaninfer/hunyuan-infer-vllm-cuda12.4:v1
 ```
 - 下载模型文件：
         --net=host \
         --gpus=all \
         -it \
+        --entrypoint python3 hunyuaninfer/hunyuan-infer-vllm-cuda12.4:v1 \
         -m vllm.entrypoints.openai.api_server \
         --host 0.0.0.0 \
         --tensor-parallel-size 4 \
         --net=host \
         --gpus=all \
         -it \
+        --entrypoint python3 hunyuaninfer/hunyuan-infer-vllm-cuda12.4:v1 \
         -m vllm.entrypoints.openai.api_server \
         --host 0.0.0.0 \
         --tensor-parallel-size 4 \