Instructions to use jrjyc1/trainee with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jrjyc1/trainee with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jrjyc1/trainee", 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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README.md
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- ProGamerGov/StableDiffusion-v1-5-Regularization-Images
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- dnlpy/Stable-Diffusion
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- yuvalkirstain/runwayml-stable-diffusion-v1-5-eval-random-prompts
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- fka/awesome-chatgpt-prompts
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- b-mc2/sql-create-context
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- Gustavosta/Stable-Diffusion-Prompts
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- sinanisler/StableDiffusion
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metrics:
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- accuracy
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- ProGamerGov/StableDiffusion-v1-5-Regularization-Images
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- dnlpy/Stable-Diffusion
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- yuvalkirstain/runwayml-stable-diffusion-v1-5-eval-random-prompts
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- sinanisler/StableDiffusion
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metrics:
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- accuracy
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