Instructions to use 12ss33/4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 12ss33/4 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("12ss33/4") 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-1500/optimizer.bin from 12ss33/4: direct link, hf CLI and curl.
- Browser
- Download file 1.18 GB
-
https://huggingface.co/12ss33/4/resolve/main/checkpoint-1500/optimizer.bin
- Command line
-
hf download hf://12ss33/4/checkpoint-1500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/12ss33/4/resolve/main/checkpoint-1500/optimizer.bin
1.18 GB
- Xet hash:
- bc046e2ad2afc22586f6a6322087f964dbe9c37f209f5d1406f96fd5c09bccc6
- Size of remote file:
- 1.18 GB
- SHA256:
- 8e6f2d4b525cae61c9a1d85b6cebaa71db00918ccaa583a313b602fc17118764
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