huggingface / huggingface/diffusers

Ability to select the strength of the safety_checker

Abierto
#9,003 1 comentario 0 reacciones 0 asignados Ver en GitHub
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Lenguaje dominante
Python
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Forks
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Merge medio
3 d 3 h
PR fusionados (30 d)
91

Descripción

**Is your feature request related to a problem? Please describe.**
Safety_checker can currently only be turned on/off, and we would like to be able to configure it in more detail.

**Describe alternatives you've considered.**
[I made it based on StableDiffusionPipeline.](https://github.com/suzukimain/diffusers/tree/edit_safety_checker)

**Describe the solution you'd like.**
I would like to be able to specify this in any pipeline using a parameter such as `safety_Level`.

```python
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
safety_Level="MAX"
).to("cuda")
```

**Additional context.**
```python

git clone https://github.com/suzukimain/diffusers.git -b edit_safety_checker ./diffusers
pip install ./diffusers

import torch
from diffusers import StableDiffusionPipeline

pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
).to("cuda")

"""
About safety_Level.
`int` or `float` or one of the following
'WEAK',
'MEDIUM',
'NOMAL',
'STRONG',
'MAX'.
"""

#-------------
#To see the filter strength.
pipe.safety_checker.safety_Level() # 0.0 (default)

#--------------
#If you want to change the intensity.
pipe.safety_checker_Level("STRONG", pipe.safety_checker)
pipe.safety_checker.safety_Level() # 0.1

#--------------
# If numbers are used
pipe.safety_checker_Level(3.0, pipe.safety_checker)
pipe.safety_checker.safety_Level() # 3.0

```

It is related to #5623.

Also, I wasn't sure what range of numbers to put in for `adjustment`, so I put -0.2~0.2 for once.
(If possible, I would appreciate it if someone could tell me about the range of `adjustment`.)

Guía de contribución

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Línea de trabajo

Start with StableDiffusionPipeline and its safety_checker, then compare the edit_safety_checker branch linked in the issue. Clarify the accepted named and numeric ranges, including adjustment, before assessing a consistent pipeline parameter; done means a pipeline can configure filter strength beyond simple enable/disable behavior.

Escrito por el modelo de indexación a partir del texto del issue.

Evaluación

Stack tecnológico
python, pytorch
Área
ai, machine-learning, security
Tipo de issue
Nueva funcionalidad
Dificultad
5/5
Tiempo estimado
Más de una semana
Estado de actividad
Estancado
Claridad
Bastante claro
Aptitud para principiantes
25/100

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