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-100/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-100/scheduler.bin
- Command line
-
hf download hf://nakkati/lrscheduler_linear/checkpoint-100/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/nakkati/lrscheduler_linear/resolve/main/checkpoint-100/scheduler.bin
1 kB
- Xet hash:
- 714cceed5057194f264bbe03f425ea82b7f61e4997668700cb2f4e8042a88757
- Size of remote file:
- 1 kB
- SHA256:
- b00b6750f12fe2f531c6b3424d7aee4ccbf910f8530c834078c8a5c72a7ea5e6
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