Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use gchen019/cat1_weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gchen019/cat1_weights with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gchen019/cat1_weights", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-500/optimizer.bin from gchen019/cat1_weights: direct link, hf CLI and curl.
- Browser
- Download file 6.88 GB
-
https://huggingface.co/gchen019/cat1_weights/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://gchen019/cat1_weights/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/gchen019/cat1_weights/resolve/main/checkpoint-500/optimizer.bin
6.88 GB
- Xet hash:
- 9c642cacab896005d35aa76e395558afa2b94d8a656ec9c89c9e2e01eca661e5
- Size of remote file:
- 6.88 GB
- SHA256:
- 92b53ce143b7612c0d5dfcf9eb22dd35334cce2735635328ff19b1fd88b2cc5d
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