Text Generation
Transformers
Safetensors
English
qwen2
nf4
asset-editor
stealth
prompt-enhancer
conversational
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use Veetance/Narrative-Brain-5B-NF4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Veetance/Narrative-Brain-5B-NF4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Veetance/Narrative-Brain-5B-NF4") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Veetance/Narrative-Brain-5B-NF4") model = AutoModelForCausalLM.from_pretrained("Veetance/Narrative-Brain-5B-NF4") 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
- vLLM
How to use Veetance/Narrative-Brain-5B-NF4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Veetance/Narrative-Brain-5B-NF4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Veetance/Narrative-Brain-5B-NF4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Veetance/Narrative-Brain-5B-NF4
- SGLang
How to use Veetance/Narrative-Brain-5B-NF4 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 "Veetance/Narrative-Brain-5B-NF4" \ --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": "Veetance/Narrative-Brain-5B-NF4", "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 "Veetance/Narrative-Brain-5B-NF4" \ --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": "Veetance/Narrative-Brain-5B-NF4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Veetance/Narrative-Brain-5B-NF4 with Docker Model Runner:
docker model run hf.co/Veetance/Narrative-Brain-5B-NF4
Narrative-Brain-9B-NF4
This repository contains the local Narrative Brain runtime used by the Asset Editor Stealth refine path.
Model Details
- Runtime name: Narrative Brain 9B
- Actual checkpoint class: compact Qwen2-family causal LM
- Quantization: NF4 via bitsandbytes
- Primary use: prompt refinement, prompt enhancement, and in-house narrative steering inside the Asset Editor stack
- License: Apache-2.0
Runtime Notes
- The repository preserves the historical
narrative_brain_9bpath name used by the app. - The current checkpoint is a compact runtime, not a full 9B-class Qwen block.
- Local logs identify the repaired architecture as
Qwen2ForCausalLMafter removal of an incorrect Qwen3 wrapper.
Included Runtime Components
model.safetensorsconfig.jsongeneration_config.jsonchat_template.jinjaspecial_tokens_map.jsonvocab.jsonmerges.txttokenizer.jsontokenizer_config.json
Integration
Optimized for the Veetance Asset Editor Stealth refine runtime.
Links
- Qwen family reference: Qwen/Qwen2.5-1.5B-Instruct
- Core engine: Veetance Asset Editor
- Triage and development: Asset Editor GitHub
This repository mirrors the working local runtime bundle under models/narrative_brain_9b.
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