Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
4.9 KiB
+++ disableToc = false title = "🧨 Diffusers" weight = 4 +++
Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. LocalAI has a diffusers backend which allows image generation using the diffusers
library.
(Generated with AnimagineXL)
Note: currently only the image generation is supported. It is experimental, so you might encounter some issues on models which weren't tested yet.
Setup
This is an extra backend - in the container is already available and there is nothing to do for the setup.
Model setup
The models will be downloaded the first time you use the backend from huggingface
automatically.
Create a model configuration file in the models
directory, for instance to use Linaqruf/animagine-xl
with CPU:
name: animagine-xl
parameters:
model: Linaqruf/animagine-xl
backend: diffusers
# Force CPU usage - set to true for GPU
f16: false
diffusers:
pipeline_type: StableDiffusionXLPipeline
cuda: false # Enable for GPU usage (CUDA)
scheduler_type: euler_a
Local models
You can also use local models, or modify some parameters like clip_skip
, scheduler_type
, for instance:
name: stablediffusion
parameters:
model: toonyou_beta6.safetensors
backend: diffusers
step: 30
f16: true
diffusers:
pipeline_type: StableDiffusionPipeline
cuda: true
enable_parameters: "negative_prompt,num_inference_steps,clip_skip"
scheduler_type: "k_dpmpp_sde"
cfg_scale: 8
clip_skip: 11
Configuration parameters
The following parameters are available in the configuration file:
Parameter | Description | Default |
---|---|---|
f16 |
Force the usage of float16 instead of float32 |
false |
step |
Number of steps to run the model for | 30 |
cuda |
Enable CUDA acceleration | false |
enable_parameters |
Parameters to enable for the model | negative_prompt,num_inference_steps,clip_skip |
scheduler_type |
Scheduler type | k_dpp_sde |
cfg_scale |
Configuration scale | 8 |
clip_skip |
Clip skip | None |
pipeline_type |
Pipeline type | StableDiffusionPipeline |
There are available several types of schedulers:
Scheduler | Description |
---|---|
ddim |
DDIM |
pndm |
PNDM |
heun |
Heun |
unipc |
UniPC |
euler |
Euler |
euler_a |
Euler a |
lms |
LMS |
k_lms |
LMS Karras |
dpm_2 |
DPM2 |
k_dpm_2 |
DPM2 Karras |
dpm_2_a |
DPM2 a |
k_dpm_2_a |
DPM2 a Karras |
dpmpp_2m |
DPM++ 2M |
k_dpmpp_2m |
DPM++ 2M Karras |
dpmpp_sde |
DPM++ SDE |
k_dpmpp_sde |
DPM++ SDE Karras |
dpmpp_2m_sde |
DPM++ 2M SDE |
k_dpmpp_2m_sde |
DPM++ 2M SDE Karras |
Pipelines types available:
Pipeline type | Description |
---|---|
StableDiffusionPipeline |
Stable diffusion pipeline |
StableDiffusionImg2ImgPipeline |
Stable diffusion image to image pipeline |
StableDiffusionDepth2ImgPipeline |
Stable diffusion depth to image pipeline |
DiffusionPipeline |
Diffusion pipeline |
StableDiffusionXLPipeline |
Stable diffusion XL pipeline |
Usage
Text to Image
Use the image
generation endpoint with the model
name from the configuration file:
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "<positive prompt>|<negative prompt>",
"model": "animagine-xl",
"step": 51,
"size": "1024x1024"
}'
Image to Image
https://huggingface.co/docs/diffusers/using-diffusers/img2img
An example model (GPU):
name: stablediffusion-edit
parameters:
model: nitrosocke/Ghibli-Diffusion
backend: diffusers
step: 25
f16: true
diffusers:
pipeline_type: StableDiffusionImg2ImgPipeline
cuda: true
enable_parameters: "negative_prompt,num_inference_steps,image"
IMAGE_PATH=/path/to/your/image
(echo -n '{"image": "'; base64 $IMAGE_PATH; echo '", "prompt": "a sky background","size": "512x512","model":"stablediffusion-edit"}') |
curl -H "Content-Type: application/json" -d @- http://localhost:8080/v1/images/generations
Depth to Image
https://huggingface.co/docs/diffusers/using-diffusers/depth2img
name: stablediffusion-depth
parameters:
model: stabilityai/stable-diffusion-2-depth
backend: diffusers
step: 50
# Force CPU usage
f16: true
diffusers:
pipeline_type: StableDiffusionDepth2ImgPipeline
cuda: true
enable_parameters: "negative_prompt,num_inference_steps,image"
cfg_scale: 6
(echo -n '{"image": "'; base64 ~/path/to/image.jpeg; echo '", "prompt": "a sky background","size": "512x512","model":"stablediffusion-depth"}') |
curl -H "Content-Type: application/json" -d @- http://localhost:8080/v1/images/generations