Instructions to use adtyn1345/Image_Generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use adtyn1345/Image_Generator with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("adtyn1345/Image_Generator", 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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Download README.md from adtyn1345/Image_Generator: direct link, hf CLI and curl.
- Browser
- Download file 444 Bytes
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https://huggingface.co/adtyn1345/Image_Generator/resolve/main/README.md
- Command line
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hf download hf://adtyn1345/Image_Generator/README.md
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curl -L -o README.md https://huggingface.co/adtyn1345/Image_Generator/resolve/main/README.md
444 Bytes
| license: creativeml-openrail-m | |
| tags: | |
| - NxtWave-GenAI-Webinar | |
| - text-to-image | |
| - stable-diffusion | |
| ### Dreambooth model trained by adtyn1345 following the "Build your own Gen AI model" session by NxtWave. | |
| Project Submission Code: U22IB002 | |
| Sample pictures of this concept: | |
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