Text Generation
Transformers
Safetensors
English
lightning
conversational
generative
fast
efficient
great
tasks
agent
gpt
text-generation-inference
art
custom_code
Instructions to use Aobangaming/luna-1.5-flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aobangaming/luna-1.5-flash with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Aobangaming/luna-1.5-flash", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Aobangaming/luna-1.5-flash", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Aobangaming/luna-1.5-flash with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Aobangaming/luna-1.5-flash" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Aobangaming/luna-1.5-flash", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Aobangaming/luna-1.5-flash
- SGLang
How to use Aobangaming/luna-1.5-flash 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 "Aobangaming/luna-1.5-flash" \ --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": "Aobangaming/luna-1.5-flash", "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 "Aobangaming/luna-1.5-flash" \ --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": "Aobangaming/luna-1.5-flash", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Aobangaming/luna-1.5-flash with Docker Model Runner:
docker model run hf.co/Aobangaming/luna-1.5-flash
Download model.safetensors from Aobangaming/luna-1.5-flash: direct link, hf CLI and curl.
- Browser
- Download file 173 MB
-
https://huggingface.co/Aobangaming/luna-1.5-flash/resolve/main/model.safetensors
- Command line
-
hf download hf://Aobangaming/luna-1.5-flash/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Aobangaming/luna-1.5-flash/resolve/main/model.safetensors
173 MB
- Xet hash:
- cbe41f96c8e2b86f74c064b9dbd2494f4a0c88d117dfaabcea4eb538dff7c995
- Size of remote file:
- 173 MB
- SHA256:
- 8ee65b783e97db03f9167748c7f4e636eed773aa48474aabdbef45dece730893
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