huggingface / huggingface/diffusers

support TextDiffuser pipelines natively in Diffusers

Abierto
#8,410 5 comentarios 0 reacciones 0 asignados Ver en GitHub
contributions-welcome stale
Lenguaje dominante
Python
Estrellas
34.5k
Forks
7.3k
Merge medio
3 d 3 h
PR fusionados (30 d)
91

Descripción

### Model/Pipeline/Scheduler description

![image](https://github.com/microsoft/unilm/raw/master/textdiffuser/assets/readme_images/introduction.jpg)

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

Abrir la 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

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