TIGMaN Text To Image
TIGMaN is a new cutting-edge image generation model based on the Stable Diffusion 1.5 architecture. TIGMaN is trained exclusively on public domain images, allowing it to be a robust and versatile model while ensuring...
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 470 MB
- Versión
- vpytorch_model
- Actualizado
- 6 oct 2026
- Fuente
- Hugging Face
Descripción de la fuente
image/jpeg
TIGMaN AI - Trained Image Generation Model and Neural AI
TIGMaN is a new cutting-edge image generation model based on the Stable Diffusion 1.5 architecture. TIGMaN is trained exclusively on public domain images, allowing it to be a robust and versatile model while ensuring that it is avaliable for unrestricted use.
Limitations
TIGMaN may face challenges in generating highly detailed or text-reliant images due to the constraints of permissive content datasets. Additionally, TIGMaN may carry biases encountered on the datasets used for training.
Datasets/Sources Used For Training
TIGMaN is trained on images and content from the following sources:
- Pexels: Pexels License (Public Domain)
- LIBRESHOT: CC0 (Public Domain)
- Unsplash: Lite Dataset License (Public Domain)
- opengameart.org: CC0 (Public Domain)
- Authors: CC0 (Public Domain)
- Contributors: CC0 (Public Domain)
- Met Museum Open Access CC0 (Public Domain)
Intended Uses
- Generative art
- Experiments on generative AI
- Research on the limits of the public domain
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 6 oct
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
2 extractos
Extractos de fuentes
2 extractos--- license: apache-2.0 language: - en pipeline_tag: text-to-image tags: - safetensors - diffusers - image-generation - stable-diffusion ---  ## TIGMaN AI - Trained Image Generation Model and Neural AI TIGMaN is a new cutting-edge image generation model based on the Stable Diffusion 1.5 architecture. TIGMaN is trained exclusively on public domain images, allowing it to be a robust and versatile model while ensuring that it is avaliable for unrestricted use. ## Limitations TIGMaN may face challenges in generating highly detailed or text-reliant images due to the constraints of permissive content datasets. Additionally, TIGMaN may carry biases encountered on the datasets used for training. ## Datasets/Sources Used For Training TIGMaN is trained on images and content from the following sources: - **Pexels:** Pexels License (Public Domain) - **LIBRESHOT:** CC0 (Public Domain) - **Unsplash:** Lite Dataset License (Public Domain) - **opengameart.org:** CC0 (Public Domain) - **Authors:** CC0 (Public Domain) - **Contributors:** CC0 (Public Domain) - **Met Museum Open Access** CC0 (Public Domain) ## Intended Uses * Generative art * Experiments on generative AI * Research on the limits of the public domain
Source context: 21 downloads · 1 likes · Pipeline text-to-image · Library diffusers · Repo Keynote-Technology/TIGMaN-text-to-image
