🌌 Illuma - Truly Open Source Image Generation
Illuma is an image generation model cloned from Salesforce/BLIP3o-NEXT-GRPO-TexT-3B — the first truly open-source image generation model with:
- ✅ Training code released (Apache 2.0)
- ✅ Datasets released (BLIP3o-Pretrain + BLIP3o-60K)
- ✅ No usage restrictions (Apache 2.0 license)
- ✅ Can be renamed, rebranded, and refined
Architecture
AR (3B Qwen2.5-VL) + SANA 1.5 Diffusion Decoder
Illuma uses a two-stage generation process:
- Autoregressive model generates visual tokens from text prompt
- SANA 1.5 diffusion decoder converts visual tokens to a high-quality image
The GRPO (Group Relative Policy Optimization) RL training improves text rendering in generated images (GenEval 0.73 → 0.90).
🚀 Deploy on Hugging Face Inference Endpoints
This model includes a custom handler (handler.py) for deployment on HF Inference Endpoints:
- Go to Inference Endpoints
- Click "+ New endpoint"
- Select
fuhaddesmond/illumaas the model repository - Select AWS → NVIDIA T4 ($0.50/hr) or NVIDIA A10G ($1.00/hr)
- Set Task to Custom
- Click Create Endpoint
- Once deployed, call the API:
import requests
API_URL = "https://YOUR_ENDPOINT_ID.aws.endpoints.huggingface.cloud"
headers = {"Authorization": "Bearer hf_YOUR_TOKEN"}
payload = {
"inputs": "A neon sign that says 'ILLUMA' glowing in purple against a dark wall",
"parameters": {
"seq_len": 729,
"top_p": 0.95,
"top_k": 1200
}
}
response = requests.post(API_URL, headers=headers, json=payload)
import base64
from PIL import Image
from io import BytesIO
image_data = base64.b64decode(response.json()["image"])
image = Image.open(BytesIO(image_data))
image.save("illuma_output.png")
🔧 Local Inference
# Clone BLIP3o repo (BLIP3o-NEXT branch)
git clone --branch BLIP3o-NEXT --single-branch https://github.com/JiuhaiChen/BLIP3o.git
cd BLIP3o
pip install -e .
# Download model
python -c "from huggingface_hub import snapshot_download; print(snapshot_download(repo_id='fuhaddesmond/illuma', repo_type='model'))"
# Run inference
python inference.py /path/to/downloaded/model
Download
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="fuhaddesmond/illuma",
repo_type="model"
)
Model Details
| Detail | Value |
|---|---|
| Base Model | BLIP3o-NEXT-GRPO-TexT-3B |
| Parameters | ~4B (3B AR + diffusion decoder) |
| Architecture | Qwen2.5-VL + SANA 1.5 |
| License | Apache 2.0 |
| GRPO Training | GenEval 0.73 → 0.90 |
| Specialty | Text rendering in images |
Citation
@article{chen2025blip3,
title={BLIP3-o: A Family of Fully Open Unified Multimodal Models},
author={Chen, Jiuhai and others},
journal={arXiv preprint arXiv:2505.09568},
year={2025}
}