Instructions to use emilianJR/AnyLORA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use emilianJR/AnyLORA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("emilianJR/AnyLORA", 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 unet/diffusion_pytorch_model.bin from emilianJR/AnyLORA: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/emilianJR/AnyLORA/resolve/2e58279892c4f694c8e473ede10d5f1ae8f25986/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://emilianJR/AnyLORA@2e58279892c4f694c8e473ede10d5f1ae8f25986/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/emilianJR/AnyLORA/resolve/2e58279892c4f694c8e473ede10d5f1ae8f25986/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 6f86690574579782473e1d3bf75cf72b17ea4a31bc8dbd815c59bb31f6e071a5
- Size of remote file:
- 3.44 GB
- SHA256:
- 634716e2c2e36bcafc1bf7fa788d627f552f00cf782c89a0b36aad778033e42c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.