Instructions to use osanseviero/huggingface2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use osanseviero/huggingface2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("osanseviero/huggingface2", 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 osanseviero/huggingface2: direct link, hf CLI and curl.
- Browser
- Download file 2.24 kB
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https://huggingface.co/osanseviero/huggingface2/resolve/refs%2Fpr%2F3/README.md
- Command line
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hf download hf://osanseviero/huggingface2@refs/pr/3/README.md
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curl -L -o README.md https://huggingface.co/osanseviero/huggingface2/resolve/refs%2Fpr%2F3/README.md
2.24 kB
| license: creativeml-openrail-m | |
| tags: | |
| - text-to-image | |
| ### huggingface2 Dreambooth model trained by osanseviero with [Hugging Face Dreambooth Training Space](https://huggingface.co/spaces/multimodalart/dreambooth-training) | |
| You run your new concept via `diffusers` [Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb). Don't forget to use the concept prompts! | |
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| huggingface emoji (use that on your prompt) | |
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