Instructions to use cat666/VToooo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cat666/VToooo with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cat666/VToooo", 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
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Use sd1.5 to fine tune,
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I used nearly 200,000 data for training, learning_rate 5e-6, training with a6000x1, epoch 10, because I am too busy recently, I should not be able to actively do it, and the funds are slightly insufficient
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,Forget it, I'm overtraining, take it as an interesting model
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inference: true
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I used nearly 200,000 data for training, learning_rate 5e-6, training with a6000x1, epoch 10, because I am too busy recently, I should not be able to actively do it, and the funds are slightly insufficient
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,Forget it, I'm overtraining, take it as an interesting model
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