Instructions to use Baptlem/UCDR-Net_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Baptlem/UCDR-Net_models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Baptlem/UCDR-Net_models", 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
Rename coyo2M-bridge3M/readme.md to coyo1M-bridge2M/readme.md
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- coyo2M-bridge3M/readme.md +0 -2
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Repo for controlnet model trained on 1M samples from coyo-700M dataset and 2M samples from bridge dataset
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Concatenate meta.jsonl of 1M coyo samples with meta.jsonl of 2M bridge samples
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Repo for controlnet model trained on 2M samples from coyo-700M dataset and 3M samples from bridge dataset
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Concatenate meta.jsonl of 2M coyo samples with meta.jsonl of 3M bridge samples
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