Text Generation
Transformers
Safetensors
mistral
mergekit
Merge
roleplay
conversational
text-generation-inference
Instructions to use Vortex5/Luminous-Shadow-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vortex5/Luminous-Shadow-12B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Vortex5/Luminous-Shadow-12B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Vortex5/Luminous-Shadow-12B") model = AutoModelForCausalLM.from_pretrained("Vortex5/Luminous-Shadow-12B", 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 Vortex5/Luminous-Shadow-12B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Vortex5/Luminous-Shadow-12B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Vortex5/Luminous-Shadow-12B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Vortex5/Luminous-Shadow-12B
- SGLang
How to use Vortex5/Luminous-Shadow-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/Luminous-Shadow-12B" \ --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": "Vortex5/Luminous-Shadow-12B", "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 "Vortex5/Luminous-Shadow-12B" \ --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": "Vortex5/Luminous-Shadow-12B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Vortex5/Luminous-Shadow-12B with Docker Model Runner:
docker model run hf.co/Vortex5/Luminous-Shadow-12B
metadata
base_model:
- Retreatcost/Ollpheist-12B
- Vortex5/Shadow-Crystal-12B
- Retreatcost/KansenSakura-Radiance-RP-12b
- Vortex5/MegaMoon-Karcher-12B
library_name: transformers
tags:
- mergekit
- merge
- roleplay
Luminous-Shadow-12B
“Within the deepest shadow, the brightest light awaits.”
✨ Overview
Luminous-Shadow-12B was merged using the DELLA merge method via MergeKit, balancing ethereal creativity and reasoned coherence.
It draws from the expressive nature of Shadow-Crystal, the refined structure of KansenSakura-Radiance-RP, and the stylistic artistry of Ollpheist.
It draws from the expressive nature of Shadow-Crystal, the refined structure of KansenSakura-Radiance-RP, and the stylistic artistry of Ollpheist.
🪶 Merge Configuration
Show Config
models:
- model: Retreatcost/KansenSakura-Radiance-RP-12b
parameters:
weight:
- filter: self_attn
value: [0.2, 0.25, 0.35, 0.55, 0.7, 0.8, 0.65, 0.4]
- filter: mlp
value: [0.25, 0.35, 0.25, 0.44]
- filter: norm
value: 0.35
- value: 0.40
density: 0.45
epsilon: 0.25
- model: Retreatcost/Ollpheist-12B
parameters:
weight:
- filter: self_attn
value: [0.0, 0.1, 0.25, 0.45, 0.55, 0.45, 0.25, 0.1]
- filter: mlp
value: [0.0, 0.15, 0.3, 0.5, 0.7, 0.55, 0.35, 0.15]
- filter: norm
value: 0.25
- filter: lm_head
value: 0.4
- value: 0.25
density: 0.4
epsilon: 0.35
- model: Vortex5/Shadow-Crystal-12B
parameters:
weight:
- filter: self_attn
value: [0.2, 0.2, 0.15, 0.35, 0.55, 0.55, 0.25, 0.6]
- filter: mlp
value: [0.0, 0.1, 0.25, 0.5, 0.4, 0.4, 0.65, 0.65]
- filter: lm_head
value: 0.55
- filter: norm
value: 0.15
- value: 0.15
density: 0.35
epsilon: 0.25
merge_method: della
base_model: Vortex5/MegaMoon-Karcher-12B
parameters:
lambda: 1.0
normalize: true
dtype: bfloat16
tokenizer:
source: Retreatcost/KansenSakura-Radiance-RP-12b
🪄Intended Use
🧘 Reflective dialogue • 🖋️ Creative writing • 💞 Character roleplay — blending emotion, intellect, and style into a single expressive voice.
✨ Acknowledgements
- ⚙️ mradermacher — static / imatrix quantization
- 🜛 DeathGodlike — EXL3 quants
- 🌟 All original authors and contributors whose models formed the foundation for this merge
