Instructions to use MeowFR/vynrelle-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MeowFR/vynrelle-lora 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("MeowFR/vynrelle-lora") prompt = "vynrelle, close-up portrait, front view, smile" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download optimizer.pt from MeowFR/vynrelle-lora: direct link, hf CLI and curl.
- Browser
- Download file 350 MB
-
https://huggingface.co/MeowFR/vynrelle-lora/resolve/main/optimizer.pt
- Command line
-
hf download hf://MeowFR/vynrelle-lora/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/MeowFR/vynrelle-lora/resolve/main/optimizer.pt
350 MB
- Xet hash:
- 27b73713e4d132395d169e2a038395715658dd9514d13228bdc395f277d18796
- Size of remote file:
- 350 MB
- SHA256:
- 827d413d9366d1668f9be250fec5fa5278e950d9a064977473fdbfe16e7f8f0f
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