Instructions to use loyal-misc/portalchambers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use loyal-misc/portalchambers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LyliaEngine/Pony_Diffusion_V6_XL", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("loyal-misc/portalchambers") prompt = "Portal2, testchamber, box, light, white background, empty, complex, futuristic, sci-fi, science fiction, game, video game, blue red green yellow dark black, intricate lines, hard edges, perfect, masterpiece, microscopic detail, miniature, figurine style, circle, oval, dodecahedron, brick, concrete background, serene, important, impressive, image, jpeg, 16:9,9:16,1:1,?" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Upload 3 files
#1
by loyal-misc - opened
images/Portal2 testchamber result pictures.tar
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version https://git-lfs.github.com/spec/v1
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oid sha256:3abc728f87e45a11240c9a8340574efcfe28eb07017e0f0b76ef38473592b46a
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size 38264832
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images/Training Params.txt
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{
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"engine": "kohya",
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"unetLR": 0.05,
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"clipSkip": 1,
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"loraType": "lora",
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"keepTokens": 1,
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"networkDim": 8,
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"numRepeats": 1,
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"resolution": 768,
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"lrScheduler": "cosine",
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"minSnrGamma": 5,
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"noiseOffset": 0.1,
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"targetSteps": 1480,
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"enableBucket": true,
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"networkAlpha": 8,
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"optimizerType": "Prodigy",
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"textEncoderLR": 0.005,
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"maxTrainEpochs": 40,
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"shuffleCaption": true,
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"trainBatchSize": 1,
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"flipAugmentation": true,
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"lrSchedulerNumCycles": 3
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}
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images/training_data.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:360ea64a7a686dd5ebebe432f6afeef5058aff7f77b26d3e52d07ee515143a14
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size 1228032
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