Instructions to use zhyemmmm/CuriousMerge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zhyemmmm/CuriousMerge with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zhyemmmm/CuriousMerge", 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
Upload folder using huggingface_hub
Browse files- vae/config.json +1 -1
- vae/diffusion_pytorch_model.bin +1 -1
vae/config.json
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{
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"_class_name": "AutoencoderKL",
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"_diffusers_version": "0.
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"act_fn": "silu",
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"block_out_channels": [
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128,
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{
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"_class_name": "AutoencoderKL",
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"_diffusers_version": "0.18.2",
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"act_fn": "silu",
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"block_out_channels": [
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128,
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vae/diffusion_pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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oid sha256:1b01618945554d9840701d3453d4a9fe3db0db090164a5ed6305641306285b6f
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size 334712113
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