Text-to-Image
Diffusers
TensorBoard
diffusers-training
dora
template:sd-lora
stable-diffusion-xl
stable-diffusion-xl-diffusers
Instructions to use FaceSoft/cbox_LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FaceSoft/cbox_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("FaceSoft/cbox_LoRA", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of Cornell box" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-12000/scaler.pt from FaceSoft/cbox_LoRA: direct link, hf CLI and curl.
- Browser
- Download file 988 Bytes
-
https://huggingface.co/FaceSoft/cbox_LoRA/resolve/main/checkpoint-12000/scaler.pt
- Command line
-
hf download hf://FaceSoft/cbox_LoRA/checkpoint-12000/scaler.pt
-
curl -L -o scaler.pt https://huggingface.co/FaceSoft/cbox_LoRA/resolve/main/checkpoint-12000/scaler.pt
988 Bytes
- Xet hash:
- 056162b9325d76394a6e4c6457755c6118c826e4efa7f7a99fbc515784488092
- Size of remote file:
- 988 Bytes
- SHA256:
- 2d1f9d6a63312bf6188d8844a7d621f2ecda20b6c0aee9e19ddcea1c480954ba
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