huggingface / huggingface/diffusers
support TextDiffuser pipelines natively in Diffusers
- Lenguaje dominante
- Python
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Descripción
### Model/Pipeline/Scheduler description

TextDiffuser is an open-source framework and pretrained model series for generating unique depth maps that can be used to guide the model for typography.
It not only has open code and weights, but the dataset is also available, containing ~9.7 million typography samples 🤯
### Open source status
- [X] The model implementation is available.
- [X] The model weights are available (Only relevant if addition is not a scheduler).
### Provide useful links for the implementation
Original repository: https://github.com/microsoft/unilm/tree/master/textdiffuser
Follow-up repository: https://github.com/microsoft/unilm/tree/master/textdiffuser-2
Demo video (not mine): https://youtu.be/ApcJ1UyLQB8?t=62 (timestamp)
Guía de contribución
Línea de trabajo
Start by reviewing the TextDiffuser and TextDiffuser-2 repositories linked in the issue to understand the available model implementations and weights. Then inspect Diffusers' existing pipeline integration patterns. Done means TextDiffuser pipelines are supported natively in Diffusers, with the required upstream functionality and validation identified during implementation.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- python, pytorch
- Área
- machine-learning
- Tipo de issue
- Nueva funcionalidad
- Dificultad
- 5/5
- Tiempo estimado
- Más de una semana
- Estado de actividad
- Estancado
- Claridad
- Necesita aclaración
- Aptitud para principiantes
- 25/100