Instructions to use llfkf/path-to-save-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use llfkf/path-to-save-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("llfkf/path-to-save-model") prompt = "a photo of sks boy" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-600/optimizer.bin from llfkf/path-to-save-model: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/llfkf/path-to-save-model/resolve/main/checkpoint-600/optimizer.bin
- Command line
-
hf download hf://llfkf/path-to-save-model/checkpoint-600/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/llfkf/path-to-save-model/resolve/main/checkpoint-600/optimizer.bin
6.59 MB
- Xet hash:
- fc41dbd0e33e41808e17ee9e9123ca802b1e2e742f79a3aea61584ed350742f6
- Size of remote file:
- 6.59 MB
- SHA256:
- 647f1061f96f698e7f7d774b89324ec6603dd96a7f17a92c8b4fb3aa844d6551
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