Instructions to use AtlaAI/Selene-1-Mini-Llama-3.1-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AtlaAI/Selene-1-Mini-Llama-3.1-8B with Transformers:

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

pipe = pipeline("text-generation", model="AtlaAI/Selene-1-Mini-Llama-3.1-8B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AtlaAI/Selene-1-Mini-Llama-3.1-8B")
model = AutoModelForCausalLM.from_pretrained("AtlaAI/Selene-1-Mini-Llama-3.1-8B", 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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AtlaAI/Selene-1-Mini-Llama-3.1-8B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AtlaAI/Selene-1-Mini-Llama-3.1-8B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AtlaAI/Selene-1-Mini-Llama-3.1-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/AtlaAI/Selene-1-Mini-Llama-3.1-8B

SGLang

How to use AtlaAI/Selene-1-Mini-Llama-3.1-8B 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 "AtlaAI/Selene-1-Mini-Llama-3.1-8B" \
    --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": "AtlaAI/Selene-1-Mini-Llama-3.1-8B",
		"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 "AtlaAI/Selene-1-Mini-Llama-3.1-8B" \
        --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": "AtlaAI/Selene-1-Mini-Llama-3.1-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use AtlaAI/Selene-1-Mini-Llama-3.1-8B with Docker Model Runner:
```
docker model run hf.co/AtlaAI/Selene-1-Mini-Llama-3.1-8B
```

## 🚨 License Conflict

by xixi126 - opened Jun 20, 2025

Discussion

xixi126

Jun 20, 2025

Hi, I'd like to report a License Conflict in AtlaAI/Selene-1-Mini-Llama-3.1-8B. I noticed that this model appears to be fine-tuned from meta-llama/Llama-3.1-8B-Instruct, while being published under the Apache-2.0 license. Given the terms outlined in the LLaMA 3.1 Community License, especially regarding redistribution, attribution, and naming, this combination of licenses could potentially lead to legal or usage misunderstandings.

⚠️ Key violations of LLaMA 3.1 license terms:

Clause 1.b.i – Releasing derivative models must:
  • Include a copy of the original license  
  • Display “Built with Llama”  
  • Use “Llama” at the beginning of the model name  
  
Clause 1.b.iii – Must retain the following notice in the release:
   “Llama 3.1 is licensed under the Llama 3.1 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.”

🔹Suggestion:

1. It’s a good idea to explicitly include all key clauses of the LLaMA 3.1 Community License, such as:

A copy of the LLaMA 3.1 license in the repository or model card
A visible “Built with LLaMA” label on the model card, documentation, or UI
Using “LLaMA” at the beginning of the model name
A statement clarifying that use of the model must comply with Meta’s Acceptable Use Policy

2. Maybe we can just drop the Apache-2.0 tag and going with the LLaMA 3.1 Community License. This approach may help reduce potential confusion about redistribution rights and downstream usage conditions.

Thanks for your attention!

xixi126

Jul 10, 2025

Looking forward to your response!

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