Instructions to use Kiriam/beatles_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kiriam/beatles_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Kiriam/beatles_model") prompt = "a photo of sks album" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download pytorch_lora_weights.bin from Kiriam/beatles_model: direct link, hf CLI and curl.
- Browser
- Download file 3.29 MB
-
https://huggingface.co/Kiriam/beatles_model/resolve/main/pytorch_lora_weights.bin
- Command line
-
hf download hf://Kiriam/beatles_model/pytorch_lora_weights.bin
-
curl -L -o pytorch_lora_weights.bin https://huggingface.co/Kiriam/beatles_model/resolve/main/pytorch_lora_weights.bin
3.29 MB
- Xet hash:
- 549e0ac118f5c0cbe93b551b361184792952e0d7895522e49d78a6411fab98e5
- Size of remote file:
- 3.29 MB
- SHA256:
- 76f4b50dca52fb37a59db3168a3636280509d4c5105f4508e1f5186d6d0c484e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.