Instructions to use acmyu/howl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use acmyu/howl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("acmyu/howl", 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 acmyu/howl: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/acmyu/howl/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://acmyu/howl/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/acmyu/howl/resolve/main/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- 9943fad6d59eb29713870d336fda80fef5b9c435148fd5391c1c081132ab58d3
- Size of remote file:
- 681 MB
- SHA256:
- ee53710b9d07d89a55724e5dc13476af66b3d2577ec6204f06dad55eac42adb2
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