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-11000/scheduler.bin from FaceSoft/cbox_LoRA: direct link, hf CLI and curl.
- Browser
- Download file 1 kB
-
https://huggingface.co/FaceSoft/cbox_LoRA/resolve/main/checkpoint-11000/scheduler.bin
- Command line
-
hf download hf://FaceSoft/cbox_LoRA/checkpoint-11000/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/FaceSoft/cbox_LoRA/resolve/main/checkpoint-11000/scheduler.bin
1 kB
- Xet hash:
- f560fdd535ae88a7707f9ea1a06ba8b51113a62a54a96c36c2688b08f3c5e23b
- Size of remote file:
- 1 kB
- SHA256:
- 4f51f00ec9b380a3f639e5866d79afd55acb6c6b4889d71ea00923226f9b7801
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