Instructions to use SedatAl/Crypto-Punk-LoRa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SedatAl/Crypto-Punk-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("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("SedatAl/Crypto-Punk-LoRa") prompt = "pixel art cryptopunks, human, female, medium skin tone, Big Shades, Crazy Hair" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-2500/optimizer.bin from SedatAl/Crypto-Punk-LoRa: direct link, hf CLI and curl.
- Browser
- Download file 15.1 MB
-
https://huggingface.co/SedatAl/Crypto-Punk-LoRa/resolve/main/checkpoint-2500/optimizer.bin
- Command line
-
hf download hf://SedatAl/Crypto-Punk-LoRa/checkpoint-2500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/SedatAl/Crypto-Punk-LoRa/resolve/main/checkpoint-2500/optimizer.bin
15.1 MB
- Xet hash:
- c748b1eb7a51c2b94fad7c6a339aab1545ac662e8f6e9e94a5d56bab053514dc
- Size of remote file:
- 15.1 MB
- SHA256:
- c9eea2dea6bfe834567dfeb5ca5776bc064475f2428e2d499b923ae93bf06e52
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