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-2000/scheduler.bin from nakkati/lrscheduler_linear: direct link, hf CLI and curl.
- Browser
- Download file 1 kB
-
https://huggingface.co/nakkati/lrscheduler_linear/resolve/main/checkpoint-2000/scheduler.bin
- Command line
-
hf download hf://nakkati/lrscheduler_linear/checkpoint-2000/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/nakkati/lrscheduler_linear/resolve/main/checkpoint-2000/scheduler.bin
1 kB
- Xet hash:
- e630e224ca1580dcfe514e2804beda4f6029005475f662a3fdec8d7fc15fdf00
- Size of remote file:
- 1 kB
- SHA256:
- 9966ccf0f3909f289160aac13846b03f74302aa5e4c7647865728a1adf712423
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