Instructions to use Vortex5/Red-Synthesis-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vortex5/Red-Synthesis-12B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Vortex5/Red-Synthesis-12B")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Vortex5/Red-Synthesis-12B") model = AutoModelForMultimodalLM.from_pretrained("Vortex5/Red-Synthesis-12B") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Vortex5/Red-Synthesis-12B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Vortex5/Red-Synthesis-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/Red-Synthesis-12B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Vortex5/Red-Synthesis-12B
- SGLang
How to use Vortex5/Red-Synthesis-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/Red-Synthesis-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/Red-Synthesis-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/Red-Synthesis-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/Red-Synthesis-12B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Vortex5/Red-Synthesis-12B with Docker Model Runner:
docker model run hf.co/Vortex5/Red-Synthesis-12B
| models: | |
| - model: Vortex5/Scarlet-Seraph-12B | |
| - model: DreadPoor/Strawberry_Smoothie-12B-Model_Stock | |
| - model: inflatebot/MN-12B-Mag-Mell-R1 | |
| - model: Vortex5/Lunar-Nexus-12B | |
| - model: SuperbEmphasis/MN-12b-RP-Ink-RP-Longform | |
| - model: Vortex5/LunaMaid-12B | |
| - model: Vortex5/Dreamstar-12B | |
| merge_method: saef | |
| parameters: | |
| paradox: 0.40 | |
| strength: 0.88 | |
| boost: 0.28 | |
| modes: 2 | |
| dtype: bfloat16 | |
| tokenizer: | |
| source: Vortex5/Scarlet-Seraph-12B | |