license: creativeml-openrail-m
language:
- en
library_name: diffusers
pipeline_tag: text-to-image
base_model: stabilityai/stable-diffusion-2
tags:
- code
- safetensors
- stable-diffusion
- scheduler
- text_encoder
- tokenizer
- unet
- vae
inference:
parameters:
num_inference_steps: 7
guidance_scale: 3
negative_prompt: >-
(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong
anatomy, extra limb, missing limb, floating limbs, (mutated hands and
fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting,
blurry, amputation
extra_gated_prompt: >-
This model is open access and available to all, with a CreativeML OpenRAIL-M
license further specifying rights and usage.
The CreativeML OpenRAIL License specifies:
1. You can't use the model to deliberately produce nor share illegal or
harmful outputs or content
2. CompVis claims no rights on the outputs you generate, you are free to use
them and are accountable for their use which must not go against the
provisions set in the license
3. You may re-distribute the weights and use the model commercially and/or as
a service. If you do, please be aware you have to include the same use
restrictions as the ones in the license and share a copy of the CreativeML
OpenRAIL-M to all your users (please read the license entirely and carefully)
Please read the full license carefully here:
https://huggingface.co/spaces/CompVis/stable-diffusion-license
extra_gated_heading: Please read the LICENSE to access this model
Samim Kumar Patel, Pretrained Model, With proper use of best Hyperparameters for Business UseCases for Production Level & It is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input.
Introducing the pretrained Model from the base Model called stabilityai/stable-diffusion-2, which is very fast and production deployable. It is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input.
Model Details
- Developed by: Samim Kumar Patel
- Model type: Diffusion-based text-to-image generation model
- Language(s): English
- License: creativeml-openrail-m
- Model Description: This is a model that can be used to generate and modify images based on text prompts.
- Resources for more information: Follow instructions here.
Diffusers usage
pip install torch diffusers
from diffusers import StableDiffusionPipeline
import torch
model_id = "samim2024/text-to-image"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")
prompt = "a photo of an astronaut riding a horse on mars"
image = pipe(prompt).images[0]
image.save("astronaut_rides_horse.png")
Uses
Direct Use
The model is intended for research purposes only. Possible research areas and tasks include
- Safe deployment of models which have the potential to generate harmful content.
- Probing and understanding the limitations and biases of generative models.
- Generation of artworks and use in design and other artistic processes.
- Applications in educational or creative tools.
- Research on generative models.
Excluded uses are described below.
Misuse, Malicious Use, and Out-of-Scope Use
The model should not be used to intentionally create or disseminate images that create hostile or alienating environments for people. This includes generating images that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.
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:
- Generating demeaning, dehumanizing, or otherwise harmful representations of people or their environments, cultures, religions, etc.
- Intentionally promoting or propagating discriminatory content or harmful stereotypes.
- Impersonating individuals without their consent.
- Sexual content without consent of the people who might see it.
- Mis- and disinformation
- Representations of egregious violence and gore
- Sharing of copyrighted or licensed material in violation of its terms of use.
- Sharing content that is an alteration of copyrighted or licensed material in violation of its terms of use.