Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
Instructions to use MatisseVS/SD2_LoRa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MatisseVS/SD2_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-2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("MatisseVS/SD2_LoRa") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-100/optimizer.bin from MatisseVS/SD2_LoRa: direct link, hf CLI and curl.
- Browser
- Download file 4.69 MB
-
https://huggingface.co/MatisseVS/SD2_LoRa/resolve/main/checkpoint-100/optimizer.bin
- Command line
-
hf download hf://MatisseVS/SD2_LoRa/checkpoint-100/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/MatisseVS/SD2_LoRa/resolve/main/checkpoint-100/optimizer.bin
4.69 MB
- Xet hash:
- 83419eaf9243f67d4913427fea23f4464988659e58038d0a2c229cecc2ffb2d9
- Size of remote file:
- 4.69 MB
- SHA256:
- dc9aa8e78758aebca3fec53bc40d5dc171e766e0bf9c8fc7782056eb5df826d2
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