URSA-0.6B-IBQ1024

URSA-0.6B-IBQ1024 Model Card

Model Details

• Developed by: BAAI
• Model type: Text-to-Image Generation Model
• Model size: 0.6B
• Model precision: torch.float16 (FP16)
• Model resolution: 1024x1024
• Model paper: Uniform Discrete Diffusion with Metric Path for Video Generation
• Model family: BAAI-Vision-URSA
• Model Tokenizer: Emu3.5-Vision-Tokenizer
• Model Description: This is a model that can be used to generate and modify images based on text prompts.

Examples

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

pip install diffusers transformers accelerate imageio[ffmpeg]
pip install git+ssh://[email protected]/baaivision/URSA.git

Running the pipeline:

import torch
from diffnext.pipelines import URSAPipeline

model_id, height, width = "BAAI/URSA-0.6B-IBQ1024", 1024, 1024
model_args = {"torch_dtype": torch.float16, "trust_remote_code": True}
pipe = URSAPipeline.from_pretrained(model_id, **model_args)
pipe = pipe.to(torch.device("cuda"))

prompt = "The bear, calm and still, gazes upward as if lost in contemplation of the cosmos."
negative_prompt = "worst quality, low quality, inconsistent motion, static, still, blurry, jittery, distorted, ugly"

image = pipe(**locals()).frames[0]
image.save("ursa.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.