Text Generation
Transformers
Safetensors
llama
atla
evaluation
llm-as-a-judge
meta
conversational
lm-judge
text-generation-inference
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
- Transformers
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
Selene Mini API endpoint - free for April
#6
by kaikaidai - opened
For those who want to use Selene Mini without the hosting overhead, the model is now also available via our API
๐จ And weโre making API use for Selene Mini free for the rest of April.
- Start for free: https://www.atla-ai.com/sign-up
- Read the release blog: https://www.atla-ai.com/post/selene-mini-api
- Try our Guardrails cookbook: https://colab.research.google.com/github/atla-ai/atla-sdk-python/blob/main/examples/cookbooks/Atla_Selene_Mini_Guardrails.ipynb
- Join our Discord: https://discord.gg/qFCMgkGwUK