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

Libraries

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

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

pipe = pipeline("text-generation", model="tencent/Youtu-LLM-2B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("tencent/Youtu-LLM-2B")
model = AutoModelForCausalLM.from_pretrained("tencent/Youtu-LLM-2B", 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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use tencent/Youtu-LLM-2B 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"
# 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/Youtu-LLM-2B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

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

SGLang

How to use tencent/Youtu-LLM-2B 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" \
    --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/Youtu-LLM-2B",
		"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/Youtu-LLM-2B" \
        --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/Youtu-LLM-2B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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

Update README.md

#22

by Junrulu - opened Feb 24

base: refs/heads/main

←

from: refs/pr/22

Discussion Files changed

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README.md +3 -3

README.md CHANGED Viewed

@@ -38,7 +38,7 @@ base_model:
 | Youtu-LLM-2B-GGUF | Instruct model of Youtu-LLM-2B, in GGUF format | 🤗 [Model](https://huggingface.co/tencent/Youtu-LLM-2B-GGUF)|
 ## 📰 News
-- [2026.01.28] You can now directly use Youtu-LLM with [Transformers](https://github.com/huggingface/transformers/pull/43166).
 - [2026.01.07] You can now fine-tune Youtu-LLM with [ModelScope](https://mp.weixin.qq.com/s/JJtQWSYEjnE7GnPkaJ7UNA).
 - [2026.01.04] You can now fine-tune Youtu-LLM with [LlamaFactory](https://github.com/hiyouga/LlamaFactory/pull/9707).
@@ -91,7 +91,7 @@ base_model:
 This guide will help you quickly deploy and invoke the **Youtu-LLM-2B** model. This model supports "Reasoning Mode", enabling it to generate higher-quality responses through Chain of Thought (CoT).
 <details>
-<summary>Transformers below 5.0.0.dev0</summary>
 If you wish to use Youtu-LLM-2B based on earlier versions of transformers, please make sure to download the model repository before this [commit](https://huggingface.co/tencent/Youtu-LLM-2B/commit/5690998a0a4cae7a7ec970d09262745e00bb6c5c).
@@ -177,7 +177,7 @@ print(f"\n{'='*20} Final Answer {'='*20}\n{final_answer}")
 </details>
 <details>
-<summary>Transformers equals or higher than 5.0.0.dev0</summary>
 ### 1. Environment Preparation
 Ensure your Python environment has the `transformers` library installed and that the version meets the requirements.

 | Youtu-LLM-2B-GGUF | Instruct model of Youtu-LLM-2B, in GGUF format | 🤗 [Model](https://huggingface.co/tencent/Youtu-LLM-2B-GGUF)|
 ## 📰 News
+- [2026.01.28] You can now directly use Youtu-LLM with [Transformers>=5.1.0](https://github.com/huggingface/transformers/releases/tag/v5.1.0).
 - [2026.01.07] You can now fine-tune Youtu-LLM with [ModelScope](https://mp.weixin.qq.com/s/JJtQWSYEjnE7GnPkaJ7UNA).
 - [2026.01.04] You can now fine-tune Youtu-LLM with [LlamaFactory](https://github.com/hiyouga/LlamaFactory/pull/9707).
 This guide will help you quickly deploy and invoke the **Youtu-LLM-2B** model. This model supports "Reasoning Mode", enabling it to generate higher-quality responses through Chain of Thought (CoT).
 <details>
+<summary>Transformers >= 4.56.0, <= 4.57.1</summary>
 If you wish to use Youtu-LLM-2B based on earlier versions of transformers, please make sure to download the model repository before this [commit](https://huggingface.co/tencent/Youtu-LLM-2B/commit/5690998a0a4cae7a7ec970d09262745e00bb6c5c).
 </details>
 <details>
+<summary>Transformers >= 5.1.0</summary>
 ### 1. Environment Preparation
 Ensure your Python environment has the `transformers` library installed and that the version meets the requirements.