Model reference · open weights
Lumina-Next-SFT is an open-weight image model from Alpha-VLLM. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Maker | Alpha-VLLM |
|---|---|
| Type | Image models |
| Task | Text→image |
| Parameters (lead) | 1.8B |
| Runs with | diffusers |
| Released | 2024-06-20 |
| Popularity | 968 downloads / month |
| Licence | Open weights |
About
The Lumina-Next-SFT is a Next-DiT model containing 2B parameters and utilizes Gemma-2B as the text encoder, enhanced through high-quality supervised fine-tuning (SFT).
Our generative model has Next-DiT as the backbone, the text encoder is the Gemma 2B model, and the VAE uses a version of sdxl fine-tuned by stabilityai.
[2024-07-08] 🎉🎉🎉 Lumina-Next is now supported in the diffusers! Thanks to @yiyixuxu and @sayakpaul!
[2024-06-08] 🎉🎉🎉 We have released the Lumina-Next-SFT model.
[2024-05-28] We updated the Lumina-Next-T2I model to support 2K Resolution image generation.
[2024-05-16] We have converted the .pth weights to .safetensors weights. Please pull the latest code to use demo.py for inference.
[2024-05-12] We release the next version of Lumina-T2I, called Lumina-Next-T2I for faster and lower memory usage image generation model.
More checkpoints of our model will be released soon~
| Resolution | Next-DiT Parameter | Text Encoder | Prediction | Download URL |
|---|---|---|---|---|
| 1024 | 2B | Gemma-2B | Rectified Flow | hugging face |
Note: You may want to adjust the CUDA version according to your driver version.
conda create -n Lumina_T2X -y
conda activate Lumina_T2X
conda install python=3.11 pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=12.1 -c pytorch -c nvidia -y
pip install diffusers huggingface_hub
flash-attnpip install flash-attn --no-build-isolation
⭐⭐ (Recommended) you can use huggingface_cli to download our model:
huggingface-cli download --resume-download Alpha-VLLM/Lumina-Next-SFT-diffusers --local-dir /path/to/ckpt
from diffusers import LuminaText2ImgPipeline
import torch
pipeline = LuminaText2ImgPipeline.from_pretrained("/path/to/ckpt/Lumina-Next-SFT-diffusers", torch_dtype=torch.bfloat16).to("cuda")
# or you can download the model using code directly
# pipeline = LuminaText2ImgPipeline.from_pretrained("Alpha-VLLM/Lumina-Next-SFT-diffusers", torch_dtype=torch.bfloat16).to("cuda")
image = pipeline(prompt="Upper body of a young woman in a Victorian-era outfit with brass goggles and leather straps. "
"Background shows an industrial revolution cityscape with smoky skies and tall, metal structures").images[0]
From the published model card. Full card on the HuggingFace links in the sidebar.
How it works
Using it via the API
Once AxForge deploys lumina-next-sft for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (lumina-next-sft below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/images/generations \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"lumina-next-sft","prompt":"a red bicycle","size":"1024x1024"}'
Create an account — your API key is available in the console. 5M tokens/month currently included with every new account at launch.