metadata

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:

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")