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...
Modellquelle
- Art
- Other
- Dateigröße
- 470 MB
- Version
- vpytorch_model
- Aktualisiert
- 6. Okt. 2026
- Quelle
- Hugging Face
Quellenbeschreibung
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
Quellen
1 Quelle
Quellen
1 QuelleVerifiziert 6. Okt.
Modellartefakte
1 Artefakt
Modellartefakte
1 ArtefaktQuellenauszüge
2 Auszüge
Quellenauszüge
2 Auszüge--- 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
