Instructions to use Cyclone-Labs/Twilight-Embrace-31B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cyclone-Labs/Twilight-Embrace-31B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Cyclone-Labs/Twilight-Embrace-31B") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Cyclone-Labs/Twilight-Embrace-31B") model = AutoModelForMultimodalLM.from_pretrained("Cyclone-Labs/Twilight-Embrace-31B", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.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=256) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Cyclone-Labs/Twilight-Embrace-31B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Cyclone-Labs/Twilight-Embrace-31B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Cyclone-Labs/Twilight-Embrace-31B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/Cyclone-Labs/Twilight-Embrace-31B
- SGLang
How to use Cyclone-Labs/Twilight-Embrace-31B 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 "Cyclone-Labs/Twilight-Embrace-31B" \ --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": "Cyclone-Labs/Twilight-Embrace-31B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "Cyclone-Labs/Twilight-Embrace-31B" \ --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": "Cyclone-Labs/Twilight-Embrace-31B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use Cyclone-Labs/Twilight-Embrace-31B with Docker Model Runner:
docker model run hf.co/Cyclone-Labs/Twilight-Embrace-31B
Twilight-Embrace-31B
Overview
Twilight-Embrace-31B was created by combining gemma-4-31B-it, Eon-Blossom-V2-31B, Love-Aligned-31B, and Dark-Scarlett-v2.0-31B using a custom merge method.
Merge Configuration
base_model: google/gemma-4-31B-it
models:
- model: Cyclone-Labs/Eon-Blossom-V2-31B
parameters:
weight:
- filter: self_attn.q_proj.weight
value: [0.72, 0.72, 0.71, 0.7, 0.68, 0.68, 0.7, 0.71]
- filter: self_attn.k_proj.weight
value: [0.73, 0.72, 0.71, 0.7, 0.69, 0.69, 0.7, 0.72]
- filter: self_attn.v_proj.weight
value: [0.23, 0.22, 0.21, 0.2, 0.19, 0.18, 0.18, 0.19]
- filter: self_attn.o_proj.weight
value: [0.54, 0.52, 0.5, 0.48, 0.46, 0.45, 0.47, 0.5]
- filter: mlp.gate_proj.weight
value: [0.2, 0.19, 0.18, 0.17, 0.16, 0.16, 0.18, 0.2]
- filter: mlp.up_proj.weight
value: [0.2, 0.19, 0.18, 0.17, 0.16, 0.16, 0.18, 0.2]
- filter: mlp.down_proj.weight
value: [0.54, 0.52, 0.5, 0.48, 0.46, 0.45, 0.47, 0.5]
- filter: layer_scalar
value: [0.8, 0.8, 0.79, 0.78, 0.78, 0.78, 0.79, 0.8]
- filter: model.language_model.layers.
value: [0.75, 0.75, 0.74, 0.73, 0.72, 0.72, 0.73, 0.75]
- filter: language_model.embed_tokens.weight
value: 0.4
- filter: language_model.norm.weight
value: 0.8
- value: 0
- model: UnstableLlama/Love-Aligned-31B
parameters:
weight:
- filter: self_attn.q_proj.weight
value: [0.23, 0.23, 0.24, 0.25, 0.27, 0.27, 0.25, 0.24]
- filter: self_attn.k_proj.weight
value: [0.23, 0.24, 0.25, 0.26, 0.27, 0.27, 0.26, 0.24]
- filter: self_attn.v_proj.weight
value: [0.22, 0.23, 0.24, 0.25, 0.26, 0.27, 0.27, 0.26]
- filter: self_attn.o_proj.weight
value: [0.41, 0.43, 0.45, 0.47, 0.49, 0.5, 0.48, 0.45]
- filter: mlp.gate_proj.weight
value: [0.25, 0.26, 0.27, 0.28, 0.29, 0.29, 0.27, 0.25]
- filter: mlp.up_proj.weight
value: [0.25, 0.26, 0.27, 0.28, 0.29, 0.29, 0.27, 0.25]
- filter: mlp.down_proj.weight
value: [0.41, 0.43, 0.45, 0.47, 0.49, 0.5, 0.48, 0.45]
- filter: layer_scalar
value: [0.17, 0.17, 0.18, 0.19, 0.19, 0.19, 0.18, 0.17]
- filter: model.language_model.layers.
value: [0.2, 0.2, 0.21, 0.22, 0.23, 0.23, 0.22, 0.2]
- filter: language_model.embed_tokens.weight
value: 0.3
- filter: language_model.norm.weight
value: 0.17
- value: 0
- model: ReadyArt/Dark-Scarlett-v2.0-31B
parameters:
weight:
- filter: self_attn.q_proj.weight
value: 0.05
- filter: self_attn.k_proj.weight
value: 0.04
- filter: self_attn.v_proj.weight
value: 0.55
- filter: self_attn.o_proj.weight
value: 0.05
- filter: mlp.gate_proj.weight
value: 0.55
- filter: mlp.up_proj.weight
value: 0.55
- filter: mlp.down_proj.weight
value: 0.05
- filter: layer_scalar
value: 0.03
- filter: model.language_model.layers.
value: 0.05
- filter: language_model.embed_tokens.weight
value: 0.3
- filter: language_model.norm.weight
value: 0.03
- value: 0
merge_method: arcus
chat_template: auto
parameters:
gain: 0.95
inheritance: 1.1
declone: 0.15
anchor: 0.35
containment: 1.15
dtype: float32
out_dtype: bfloat16
tokenizer:
source: base
Notes
This was an interesting result. Love-Aligned-31B added a unique flavor to the merge. It is adversarial and will disagree with you in roleplay, but it seems to always seek a restorative ending in long-form story writing tests. This model can still be dark and realistic.
Intended Use
Roleplay
Character-driven interaction, personas, dialogue, emotional scenes, and long-form roleplay.
Creative Writing
Fiction, dialogue, atmosphere, descriptive writing, stylistic drafting, and imaginative prose.
Storytelling
Long-form narratives, worldbuilding, continuity, evolving characters, and multi-character plots.
Interactive Fiction
Branching narratives, scenario play, character interaction, and continuously evolving stories.
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