Instructions to use Ekkel-AI-Pvt-ltd/stable-diffusion-custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ekkel-AI-Pvt-ltd/stable-diffusion-custom with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Ekkel-AI-Pvt-ltd/stable-diffusion-custom", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Ekkel-AI-Pvt-ltd/stable-diffusion-custom", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]MODEL_CONFIG_DDIM_TRAIN
MODEL_CONFIG_DDIM = {
"_class_name": "StableDiffusionPipeline",
"_diffusers_version": "0.6.0",
"scheduler": [
"diffusers",
"DDIMScheduler"
],
"text_encoder": [
"transformers",
"CLIPTextModel"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"unet": [
"diffusers",
"UNet2DConditionModel"
],
"vae": [
"diffusers",
"AutoencoderKL"
]
}
MODEL_CONFIG_DDIM_SAVE
MODEL_CONFIG_DDIM_SAVE = {
"_class_name": "StableDiffusionPipeline",
"_diffusers_version": "0.9.0.dev0",
"scheduler": [
"diffusers",
"DDIMScheduler"
],
"text_encoder": [
"transformers",
"CLIPTextModel"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"unet": [
"diffusers",
"UNet2DConditionModel"
],
"vae": [
"diffusers",
"AutoencoderKL"
]
}
SCHEDULER_CONFIG_DDIM_TRAIN
SCHEDULER_CONFIG_DDIM_TRAIN = {
"_class_name": "DDIMScheduler",
"_diffusers_version": "0.6.0",
"beta_end": 0.012,
"beta_schedule": "scaled_linear",
"beta_start": 0.00085,
"clip_sample": false,
"num_train_timesteps": 1000,
"set_alpha_to_one": false,
"skip_prk_steps": true,
"steps_offset": 1,
"trained_betas": null
}
SCHEDULER_CONFIG_DDIM_SAVE
SCHEDULER_CONFIG_DDIM_SAVE = {
"_class_name": "DDIMScheduler",
"_diffusers_version": "0.9.0.dev0",
"beta_end": 0.012,
"beta_schedule": "scaled_linear",
"beta_start": 0.00085,
"clip_sample": false,
"num_train_timesteps": 1000,
"prediction_type": "epsilon",
"set_alpha_to_one": false,
"skip_prk_steps": true,
"steps_offset": 1,
"trained_betas": null
}
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