Instructions to use tencent/Youtu-LLM-2B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tencent/Youtu-LLM-2B-Base with Transformers:

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

pipe = pipeline("text-generation", model="tencent/Youtu-LLM-2B-Base")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("tencent/Youtu-LLM-2B-Base")
model = AutoModelForCausalLM.from_pretrained("tencent/Youtu-LLM-2B-Base", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use tencent/Youtu-LLM-2B-Base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tencent/Youtu-LLM-2B-Base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tencent/Youtu-LLM-2B-Base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/tencent/Youtu-LLM-2B-Base

SGLang

How to use tencent/Youtu-LLM-2B-Base 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/Youtu-LLM-2B-Base" \
    --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": "tencent/Youtu-LLM-2B-Base",
		"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 "tencent/Youtu-LLM-2B-Base" \
        --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": "tencent/Youtu-LLM-2B-Base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use tencent/Youtu-LLM-2B-Base with Docker Model Runner:
```
docker model run hf.co/tencent/Youtu-LLM-2B-Base
```

Junrulu commited on Jan 9

Commit

3b528d8

verified ·

1 Parent(s): 0431212

Update README.md (#8)

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@@ -37,6 +37,10 @@ instruct_model:
 | Youtu-LLM-2B | Instruct model of Youtu-LLM-2B | 🤗 [Model](https://huggingface.co/tencent/Youtu-LLM-2B)|
 | Youtu-LLM-2B-GGUF | Instruct model of Youtu-LLM-2B, in GGUF format | 🤗 [Model](https://huggingface.co/tencent/Youtu-LLM-2B-GGUF)|
 <a id="benchmarks"></a>
 ## 📊 Performance Comparisons

 | Youtu-LLM-2B | Instruct model of Youtu-LLM-2B | 🤗 [Model](https://huggingface.co/tencent/Youtu-LLM-2B)|
 | Youtu-LLM-2B-GGUF | Instruct model of Youtu-LLM-2B, in GGUF format | 🤗 [Model](https://huggingface.co/tencent/Youtu-LLM-2B-GGUF)|
+## 📰 News
+- [2026.01.07] You can now fine-tuning Youtu-LLM with [ModelScope](https://mp.weixin.qq.com/s/JJtQWSYEjnE7GnPkaJ7UNA).
+- [2026.01.04] You can now fine-tuning Youtu-LLM with [LlamaFactory](https://github.com/hiyouga/LlamaFactory/pull/9707).
 <a id="benchmarks"></a>
 ## 📊 Performance Comparisons