Text-to-Image
Diffusers
OpenVINO
StableDiffusionPipeline
modelslab.com
stable-diffusion-api
ultra-realistic
openvino-export
Instructions to use Aminfri/realistic-vision-v60-b1-openvino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Aminfri/realistic-vision-v60-b1-openvino with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Aminfri/realistic-vision-v60-b1-openvino", dtype=torch.bfloat16, device_map="cuda") prompt = "a girl wandering through the forest" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Upload vae_encoder/config.json with huggingface_hub
Browse files- vae_encoder/config.json +38 -0
vae_encoder/config.json
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{
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"_class_name": "AutoencoderKL",
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"_diffusers_version": "0.34.0",
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"_name_or_path": "/tmp/tmprns8t6gh/modelss--stablediffusionapi--realistic-vision-v60-b1/models--stablediffusionapi--realistic-vision-v60-b1/snapshots/d3be6789ddfc47e96a9e8ea98c7876b25f3879a6/vae",
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"act_fn": "silu",
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"block_out_channels": [
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128,
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256,
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512,
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512
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],
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"down_block_types": [
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"DownEncoderBlock2D",
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"DownEncoderBlock2D",
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"DownEncoderBlock2D",
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"DownEncoderBlock2D"
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],
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"force_upcast": true,
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"in_channels": 3,
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"latent_channels": 4,
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"latents_mean": null,
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"latents_std": null,
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"layers_per_block": 2,
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"mid_block_add_attention": true,
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"norm_num_groups": 32,
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"out_channels": 3,
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"sample_size": 512,
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"scaling_factor": 0.18215,
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"shift_factor": null,
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"up_block_types": [
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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"UpDecoderBlock2D",
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"UpDecoderBlock2D"
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],
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"use_post_quant_conv": true,
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"use_quant_conv": true
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}
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