Instructions to use tolgadev/tolgadreamsinbooth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tolgadev/tolgadreamsinbooth with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tolgadev/tolgadreamsinbooth", 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
Download text_encoder/pytorch_model.bin from tolgadev/tolgadreamsinbooth: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/tolgadev/tolgadreamsinbooth/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://tolgadev/tolgadreamsinbooth/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tolgadev/tolgadreamsinbooth/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- afc9a70f3b2ab278de79f8bbebc6d2eee32d8238f2cb3fc5413437d5f84da85f
- Size of remote file:
- 492 MB
- SHA256:
- 9d8a36f6087fe6f9cdc617e92231411d452f6141c3b7bca553633cd718ce0fee
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