Instructions to use sd-dreambooth-library/brime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sd-dreambooth-library/brime with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sd-dreambooth-library/brime", 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 Settings
- Draw Things
- DiffusionBee
Commit History
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Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (#3)
- Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (a34886a6d48373ef919c2599c4ee5facbf9687ff)2c2ca11
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Upload concept_images with huggingface_hub
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Upload model_index.json with huggingface_hub
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Upload vae with huggingface_hub
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Upload unet with huggingface_hub
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Upload tokenizer with huggingface_hub
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Upload text_encoder with huggingface_hub
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Upload scheduler with huggingface_hub
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Upload safety_checker with huggingface_hub
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Upload feature_extractor with huggingface_hub
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Upload the concept brime embeds and token
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initial commit
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