Vela-Lumen-15M
A 15M-parameter math content generator trained from scratch on a single 8GB laptop GPU.
Note: This is a custom architecture. Use the provided GGUF files or
inference.pyfor inference.
Downloads
| Format | File | Size | How to Use |
|---|---|---|---|
| GGUF F16 | vela-lumen-15m-f16.gguf | 16 MB | Recommended — Works with Ollama, llama.cpp, LM Studio |
| Safetensors FP16 | model-fp16.safetensors | 15 MB | Half precision, Python |
| Safetensors FP32 | model.safetensors | 31 MB | Full precision, training |
Quick Start (Ollama)
wget https://huggingface.co/ParallaxOpen/Vela-Lumen-15M/resolve/main/vela-lumen-15m-f16.gguf
cat > Modelfile << 'EOF'
FROM vela-lumen-15m-f16.gguf
TEMPLATE "{{ .System }}{{ .Prompt }}"
SYSTEM "You are a math tutor."
EOF
ollama create vela-lumen-15m -f Modelfile
ollama run vela-lumen-15m
Capabilities
What it CAN do:
- Generate math word problems and solutions
- Generate math tutorials and explanations
- Text completion for math topics
- Attempt to answer simple questions
What it CAN'T do:
- Solve arithmetic reliably (0% GSM8K)
- Complex reasoning tasks
- Long-form coherent text
Best for:
- Math content generation
- Educational content creation
- Practice problem generation
- Text completion for math topics
Model Details
| Property | Value |
|---|---|
| Developer | ParallaxOpen |
| Parameters | 15,486,080 |
| Architecture | Transformer Decoder, GQA 4:2, SwiGLU, RMSNorm, RoPE |
| Context | 512 tokens |
| Vocab | 24,189 |
| License | CC BY-NC 4.0 |
Training
- Pretrain: 200K steps on 7B tokens (1.5B web + 5.6B math)
- SFT: 3K steps on 14K math problems
- Total: ~10 hours on RTX 5060
Architecture
| Component | Value |
|---|---|
| Layers | 6 |
| Hidden dim | 320 |
| Q heads | 4 |
| KV heads | 2 (GQA) |
| FFN dim | 1,024 (SwiGLU) |
| Norm | RMSNorm |
| Position | RoPE (theta=10,000) |
| Weight tying | Yes |
Citation
@software{vela-lumen-15m,
title={Vela-Lumen-15M: A 15M-param Math Content Generator},
author={ParallaxOpen},
year={2026},
note={Trained on a single RTX 5060 Laptop GPU in 10 hours}
}