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metadata
license: apache-2.0
tags:
  - text-to-image
  - image-generation
  - baai-nova

NOVA (d48w768-sdxl1024) Model Card

Model Details

  • Developed by: BAAI
  • Model type: Masked Autoregressive Text-to-Image Generation Model
  • Model size: 363M
  • Model precision: torch.float16 (FP16)
  • Model resolution: 1024x1024
  • Model Description: This is a model that can be used to generate and modify images based on text prompts. It is a Masked Autoregressive (MAR) diffusion model that uses a pretrained text encoder (Phi-2) and one VAE image tokenizer (SDXL-VAE).
  • Model License: Apache 2.0 License
  • Resources for more information: GitHub Repository.

Examples

Using the 🤗's Diffusers library to run NOVA in a simple and efficient manner.

pip install diffusers transformers accelerate
pip install git+ssh://git@github.com/baaivision/NOVA.git

Running the pipeline:

import torch
from diffnext.pipelines import NOVAPipeline

model_id = "BAAI/nova-d48w768-sdxl1024"
model_args = {"torch_dtype": torch.float16, "trust_remote_code": True}
pipe = NOVAPipeline.from_pretrained(model_id, **model_args)
pipe = pipe.to("cuda")

prompt = "a shiba inu wearing a beret and black turtleneck."
image = pipe(prompt).images[0]
    
image.save("shiba_inu.jpg")

Uses

Direct Use

The model is intended for research purposes only. Possible research areas and tasks include

  • Research on generative models.
  • Applications in educational or creative tools.
  • Generation of artworks and use in design and other artistic processes.
  • Probing and understanding the limitations and biases of generative models.
  • Safe deployment of models which have the potential to generate harmful content.

Excluded uses are described below.

Out-of-Scope Use

The model was not trained to be factual or true representations of people or events, and therefore using the model to generate such content is out-of-scope for the abilities of this model.

Misuse and Malicious Use

Using the model to generate content that is cruel to individuals is a misuse of this model. This includes, but is not limited to:

  • Mis- and disinformation.
  • Representations of egregious violence and gore.
  • Impersonating individuals without their consent.
  • Sexual content without consent of the people who might see it.
  • Sharing of copyrighted or licensed material in violation of its terms of use.
  • Intentionally promoting or propagating discriminatory content or harmful stereotypes.
  • Sharing content that is an alteration of copyrighted or licensed material in violation of its terms of use.
  • Generating demeaning, dehumanizing, or otherwise harmful representations of people or their environments, cultures, religions, etc.

Limitations and Bias

Limitations

  • The autoencoding part of the model is lossy.
  • The model cannot render complex legible text.
  • The model does not achieve perfect photorealism.
  • The fingers, .etc in general may not be generated properly.
  • The model was trained on a subset of the web datasets LAION-5B and COYO-700M, which contains adult, violent and sexual content.

Bias

While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases.