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Text To Image

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...

TipoOtherModelo basestabilityai/stable-diffusion-2VersiónRevision a20edc7Bcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
319 MB–3,23 GB
Modelo base
stabilityai/stable-diffusion-2
Versión
vRevision a20edc7
Actualizado
6 oct 2026
Descargas
19
Fuente
Hugging Face

Descripción de la fuente

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.

preview preview

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.

Fuentes

1 fuente
Hugging FacePrincipalVersión a20edc777c2f4d126ed5d7cb8be1b30071657aa7
huggingface.co/samim2024/text-to-image/tree/a20edc777c2f4d126ed5d7cb8be1b30071657aa7

Verificado 6 oct

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Artefactos del modelo

3 artefactos

text_encoder/pytorch_model.bin

bin · 1,27 GB · SHA-256 77c4f8f5bf2c…d29b · Hugging Face

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unet/diffusion_pytorch_model.bin

bin · 3,23 GB · SHA-256 524b7417914e…bc6b · Hugging Face

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vae/diffusion_pytorch_model.bin

bin · 319 MB · SHA-256 eac6df9beeeb…38ab · Hugging Face

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Extractos de fuentes

3 extractos

--- 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.* ![preview](samples/4.jpeg) ![preview](samples/5.jpeg) 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:** Fo...

Source context: 19 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo samim2024/text-to-image

Source context: 0 downloads · 0 likes · Pipeline text-to-image · Library diffusers · Repo samim2024/text-to-image