Instructions to use Vortex5/Moonlit-Umbra-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vortex5/Moonlit-Umbra-12B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Vortex5/Moonlit-Umbra-12B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Vortex5/Moonlit-Umbra-12B") model = AutoModelForCausalLM.from_pretrained("Vortex5/Moonlit-Umbra-12B") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Vortex5/Moonlit-Umbra-12B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Vortex5/Moonlit-Umbra-12B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Vortex5/Moonlit-Umbra-12B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Vortex5/Moonlit-Umbra-12B
- SGLang
How to use Vortex5/Moonlit-Umbra-12B 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 "Vortex5/Moonlit-Umbra-12B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Vortex5/Moonlit-Umbra-12B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "Vortex5/Moonlit-Umbra-12B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Vortex5/Moonlit-Umbra-12B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Vortex5/Moonlit-Umbra-12B with Docker Model Runner:
docker model run hf.co/Vortex5/Moonlit-Umbra-12B
Moonlit-Umbra-12B
Overview
Moonlit-Umbra-12B was created by merging Muse-12B, magnum-v4-12b, NeonMaid-12B-v2, Impish_Nemo_12B, MN-Slush, Violet_Twilight-v0.2, Wayfarer-12B, MN-12B-Mag-Mell-R1, MN-12B-Celeste-V1.9, Captain-Eris_Violet-V0.420-12B, and Dans-SakuraKaze-V1.0.0-12b using a custom merge method.
Merge configuration
models: - model: LatitudeGames/Muse-12B - model: anthracite-org/magnum-v4-12b - model: yamatazen/NeonMaid-12B-v2 - model: SicariusSicariiStuff/Impish_Nemo_12B - model: crestf411/MN-Slush - model: Epiculous/Violet_Twilight-v0.2 - model: LatitudeGames/Wayfarer-12B - model: inflatebot/MN-12B-Mag-Mell-R1 - model: nothingiisreal/MN-12B-Celeste-V1.9 - model: Nitral-AI/Captain-Eris_Violet-V0.420-12B - model: PocketDoc/Dans-SakuraKaze-V1.0.0-12b merge_method: saef dtype: bfloat16 parameters: paradox: 0.45 strength: 1.0 boost: 0.5 modes: 2 tokenizer: source: Vortex5/Scarlet-Seraph-12B
Intended Use
Creative Writing
Storytelling
Roleplay
- Downloads last month
- 5
Model tree for Vortex5/Moonlit-Umbra-12B
Merge model
this model
docker model run hf.co/Vortex5/Moonlit-Umbra-12B