Instructions to use 12ss33/5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 12ss33/5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("12ss33/5") prompt = "a photo of signal heat map" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-1000/optimizer.bin from 12ss33/5: direct link, hf CLI and curl.
- Browser
- Download file 1.18 GB
-
https://huggingface.co/12ss33/5/resolve/main/checkpoint-1000/optimizer.bin
- Command line
-
hf download hf://12ss33/5/checkpoint-1000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/12ss33/5/resolve/main/checkpoint-1000/optimizer.bin
1.18 GB
- Xet hash:
- 7e0d6bc31a822520580bda4f12cb0017bafb7c6eafb9beb949b4bde304a410c9
- Size of remote file:
- 1.18 GB
- SHA256:
- bc7cbb5fe13b49b7bb89ca7522886e8e6866576fec3db72f1a4d8a605a9f76db
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