Instructions to use d1ngdongji/MCSkin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use d1ngdongji/MCSkin 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.2-klein-9B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("d1ngdongji/MCSkin") prompt = "Generate a 64x64 pixel texture maps of this Minecraft character" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- c2f2dafc3565c7d273d4a1b0e99f5a7d33d022e1f37e3ca3ae665f103322fede
- Size of remote file:
- 68.3 MB
- SHA256:
- 5074760c5677856833ef189756de137aded25fbfbe1ae9169a73d3724631811b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.