Instructions to use whaledrop/galateamodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use whaledrop/galateamodel with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("whaledrop/galateamodel", 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 whaledrop/galateamodel: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/whaledrop/galateamodel/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://whaledrop/galateamodel/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/whaledrop/galateamodel/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 953ccf946f14c510571579b1ed019150267d23a1b9de580bc7e71ed921cbad92
- Size of remote file:
- 492 MB
- SHA256:
- dd8c97197e2fdc773352ac139d134a19bd5af179658b259b7328cb6756d24f54
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