How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "fableforge-ai/NEXUS-Science"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fableforge-ai/NEXUS-Science",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/fableforge-ai/NEXUS-Science
Quick Links

NEXUS-Science

NEXUS domain specialist for scientific reasoning and research β€” lightweight & uncensored.

Downloads Demos

Base model: Qwen/Qwen2.5-1.5B-Instruct Β· Part of the FableForge ecosystem.

πŸ† Benchmarks β€” 140/150 (93%)

A 1.5B model scoring 93% β€” punching far above its weight. 30-prompt evaluation (domain knowledge, uncensored domain + general, reasoning, tool use), 0–5 scoring, run on an NVIDIA A40 via Ollama.

Category Score Avg
🎯 Domain Knowledge 47/50 4.7/5
πŸ”“ Uncensored (Domain) 25/25 5.0/5
πŸ”“ Uncensored (General) 22/25 4.4/5
🧠 Reasoning 25/25 5.0/5
πŸ”§ Tool Use 21/25 4.2/5
Total 140/150 93%

🧬 The NEXUS Family β€” six specialists, one tiny footprint

Model Score Specialty
NEXUS-Coder 141/150 Software Engineering & Code
NEXUS-Security 144/150 Cybersecurity & Hacking
NEXUS-Medical 140/150 Medicine & Healthcare
NEXUS-Legal 139/150 Law & Compliance
NEXUS-Finance 144/150 Finance & Accounting
NEXUS-Science 140/150 Science & Research

πŸ‘‰ Grab the whole family on Ollama or Hugging Face.


⚑ Run it now β€” Ollama

ollama run fableforge-ai/nexus-science:q4_k_m   # published on ollama.com
ollama run hf.co/King3Djbl/nexus-science-GGUF:Q4_K_M

πŸ“¦ GGUF quants: King3Djbl/nexus-science-GGUF

🧠 Prompt format (ChatML)

<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

🌌 See it live β€” the FableForge demos

This family powers a galaxy of free, interactive HF Spaces:


πŸ”— Related models


⭐ Like & share β€” it helps people find the source instead of a mirror.

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