Instructions to use nakkati/lrscheduler_linear with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nakkati/lrscheduler_linear 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/lrscheduler_linear") 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-500/optimizer.bin from nakkati/lrscheduler_linear: direct link, hf CLI and curl.
- Browser
- Download file 6.85 MB
-
https://huggingface.co/nakkati/lrscheduler_linear/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://nakkati/lrscheduler_linear/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/nakkati/lrscheduler_linear/resolve/main/checkpoint-500/optimizer.bin
6.85 MB
- Xet hash:
- 9ff76b44c22636899d06d2c1b98819d9dab36bf9cf6f06f52945493430814bd4
- Size of remote file:
- 6.85 MB
- SHA256:
- 16546460209b26d2538c9ece32f60800f1bd1dc7093f78461bb06b5c684cb98b
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