Instructions to use Tiiny/SmallThinker-21BA3B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Tiiny/SmallThinker-21BA3B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="Tiiny/SmallThinker-21BA3B-Instruct")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Tiiny/SmallThinker-21BA3B-Instruct", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Tiiny/SmallThinker-21BA3B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Tiiny/SmallThinker-21BA3B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Tiiny/SmallThinker-21BA3B-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Tiiny/SmallThinker-21BA3B-Instruct

SGLang

How to use Tiiny/SmallThinker-21BA3B-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 "Tiiny/SmallThinker-21BA3B-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": "Tiiny/SmallThinker-21BA3B-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 "Tiiny/SmallThinker-21BA3B-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": "Tiiny/SmallThinker-21BA3B-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Tiiny/SmallThinker-21BA3B-Instruct with Docker Model Runner:
```
docker model run hf.co/Tiiny/SmallThinker-21BA3B-Instruct
```

wdl339 commited on Jul 27, 2025

Commit

3abcff8

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Update README.md

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@@ -34,6 +34,8 @@ For the MMLU evaluation, we use a 0-shot CoT setting.
 | Gemma 3n E2B                         | 1G, theoretically   | 36.88    | 27.06     | 12.50        | 6.66           |
 | Gemma 3n E4B                         | 2G, theoretically   | 21.93    | 16.58     | 7.37         | 4.01           |
 ## Model Card
 <div align="center">

 | Gemma 3n E2B                         | 1G, theoretically   | 36.88    | 27.06     | 12.50        | 6.66           |
 | Gemma 3n E4B                         | 2G, theoretically   | 21.93    | 16.58     | 7.37         | 4.01           |
+Note：i9 14900、1+13 8ge4 use 4 threads，others use the number of threads that can achieve the maximum speed.
 ## Model Card
 <div align="center">