Instructions to use jenoh15/murre with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jenoh15/murre with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jenoh15/murre", 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
Download text_encoder/pytorch_model.bin from jenoh15/murre: direct link, hf CLI and curl.
- Browser
- Download file 1.36 GB
-
https://huggingface.co/jenoh15/murre/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://jenoh15/murre/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jenoh15/murre/resolve/main/text_encoder/pytorch_model.bin
1.36 GB
- Xet hash:
- 57a974eb535fe0475a18bdbe82a2e6af88ca379d84dd1bc48e18ec1d57ab3bec
- Size of remote file:
- 1.36 GB
- SHA256:
- e9c787e9388134c1a25dc69934a51a32a2683b38b8a9b017e1f3a692b8ed6b98
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