Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
textual_inversion
diffusers-training
Instructions to use JJSLL/Cat_Mist_object with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JJSLL/Cat_Mist_object with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_textual_inversion("JJSLL/Cat_Mist_object") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/model.safetensors from JJSLL/Cat_Mist_object: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/JJSLL/Cat_Mist_object/resolve/main/text_encoder/model.safetensors
- Command line
-
hf download hf://JJSLL/Cat_Mist_object/text_encoder/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/JJSLL/Cat_Mist_object/resolve/main/text_encoder/model.safetensors
492 MB
- Xet hash:
- a99a6661a88d7f94df5fdbafbc8718c2a5cb36d2d538c077494c444f4056bb79
- Size of remote file:
- 492 MB
- SHA256:
- 6a9a047e20c9da895758ddb3b1ad44d26ba5851a13e4beef573313fcc1ec37e6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.