Instructions to use nakkati/baseline_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nakkati/baseline_final with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("nakkati/baseline_final") prompt = "photo of Luffy, the pirate with a straw hat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-5000/optimizer.bin from nakkati/baseline_final: direct link, hf CLI and curl.
- Browser
- Download file 6.85 MB
-
https://huggingface.co/nakkati/baseline_final/resolve/main/checkpoint-5000/optimizer.bin
- Command line
-
hf download hf://nakkati/baseline_final/checkpoint-5000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/nakkati/baseline_final/resolve/main/checkpoint-5000/optimizer.bin
6.85 MB
- Xet hash:
- b5e5ec6471a4a8dbd2f1f4f1487a2e89ab516132a58e9b8ab96fffbe8bf0eb23
- Size of remote file:
- 6.85 MB
- SHA256:
- c881a0a06501f028a4913fba07aa238e7a40732a60750705f8a6cab7b1a118aa
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