Instructions to use ServiceNow-AI/Apriel-Nemotron-15b-Thinker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ServiceNow-AI/Apriel-Nemotron-15b-Thinker with Transformers:

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

pipe = pipeline("text-generation", model="ServiceNow-AI/Apriel-Nemotron-15b-Thinker")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ServiceNow-AI/Apriel-Nemotron-15b-Thinker")
model = AutoModelForCausalLM.from_pretrained("ServiceNow-AI/Apriel-Nemotron-15b-Thinker", 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 ServiceNow-AI/Apriel-Nemotron-15b-Thinker with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ServiceNow-AI/Apriel-Nemotron-15b-Thinker"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ServiceNow-AI/Apriel-Nemotron-15b-Thinker",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ServiceNow-AI/Apriel-Nemotron-15b-Thinker

SGLang

How to use ServiceNow-AI/Apriel-Nemotron-15b-Thinker 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 "ServiceNow-AI/Apriel-Nemotron-15b-Thinker" \
    --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": "ServiceNow-AI/Apriel-Nemotron-15b-Thinker",
		"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 "ServiceNow-AI/Apriel-Nemotron-15b-Thinker" \
        --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": "ServiceNow-AI/Apriel-Nemotron-15b-Thinker",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ServiceNow-AI/Apriel-Nemotron-15b-Thinker with Docker Model Runner:
```
docker model run hf.co/ServiceNow-AI/Apriel-Nemotron-15b-Thinker
```

Add this model to huggingchat!

by devopsML - opened May 12, 2025

Discussion

devopsML

May 12, 2025

Thanks for releasing this great LLM! Anyway, would you mind adding this model to huggingchat (huggingface's own chatgpt-style UI theme for open-source LLMs), since many of us highly demand this AI model?

BTW, if you want to contribute your model to huggingchat, you can add your model to huggingchat's official github repository: https://github.com/huggingface/chat-ui

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