Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
controlnet
diffusers-training
Instructions to use c-eshih/models_human with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use c-eshih/models_human with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("c-eshih/models_human") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-16500/optimizer.bin from c-eshih/models_human: direct link, hf CLI and curl.
- Browser
- Download file 2.89 GB
-
https://huggingface.co/c-eshih/models_human/resolve/main/checkpoint-16500/optimizer.bin
- Command line
-
hf download hf://c-eshih/models_human/checkpoint-16500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/c-eshih/models_human/resolve/main/checkpoint-16500/optimizer.bin
2.89 GB
- Xet hash:
- 4e7f561bb2f2171203e21eaa2360f90364a5300e41ab5317216bf38a89ed58b7
- Size of remote file:
- 2.89 GB
- SHA256:
- 725cbcafa3d9dee117002671d5521156d5ef9274d825465185f027177607be21
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.