Instructions to use layerdifforg/seethroughv0.0.1_layerdiff3d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use layerdifforg/seethroughv0.0.1_layerdiff3d with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("layerdifforg/seethroughv0.0.1_layerdiff3d", 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
File size: 1,117 Bytes
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"_class_name": "KDiffusionStableDiffusionXLPipeline",
"_diffusers_version": "0.37.0.dev0",
"feature_extractor": [
null,
null
],
"force_zeros_for_empty_prompt": true,
"image_encoder": [
null,
null
],
"requires_aesthetics_score": false,
"scheduler": [
"diffusers",
"DPMSolverMultistepScheduler"
],
"tag_list": [
"hair",
"headwear",
"face",
"eyes",
"eyewear",
"ears",
"earwear",
"nose",
"mouth",
"neck",
"neckwear",
"topwear",
"handwear",
"bottomwear",
"legwear",
"footwear",
"tail",
"wings",
"objects"
],
"text_encoder": [
"transformers",
"CLIPTextModel"
],
"text_encoder_2": [
"transformers",
"CLIPTextModelWithProjection"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"tokenizer_2": [
"transformers",
"CLIPTokenizer"
],
"trans_vae": [
"modules.layerdiffuse.vae",
"TransparentVAE"
],
"unet": [
"modules.layerdiffuse.layerdiff3d",
"UNetFrameConditionModel"
],
"vae": [
"diffusers",
"AutoencoderKL"
]
}
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