Instructions to use neggles/Andromeda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use neggles/Andromeda with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("neggles/Andromeda", dtype=torch.bfloat16, device_map="cuda") prompt = "1girl, solo, bangs, (pink hair, gradient hair, very long hair:1.1), (purple eyes:1.05), (cat ears, animal ear fluff:1.2), sidelocks, white shirt, collared shirt, buttons, night, looking at viewer, table, pizza on table, pov, restaurant, medium breasts, smiling, (blush:0.7), colored inner hair, (symmetric), (masterpiece, exceptional, extremely detailed:1.1)" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 579 Bytes
c5ed958 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | {
"_class_name": "StableDiffusionPipeline",
"_diffusers_version": "0.16.1",
"feature_extractor": [
"transformers",
"CLIPFeatureExtractor"
],
"requires_safety_checker": true,
"safety_checker": [
"stable_diffusion",
"StableDiffusionSafetyChecker"
],
"scheduler": [
"diffusers",
"PNDMScheduler"
],
"text_encoder": [
"transformers",
"CLIPTextModel"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"unet": [
"diffusers",
"UNet2DConditionModel"
],
"vae": [
"diffusers",
"AutoencoderKL"
]
}
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