Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
custom-diffusion
diffusers-training
Instructions to use Andy9310/saved_cat2_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Andy9310/saved_cat2_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Andy9310/saved_cat2_model", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of <cat2>" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-2000/optimizer.bin from Andy9310/saved_cat2_model: direct link, hf CLI and curl.
- Browser
- Download file 457 MB
-
https://huggingface.co/Andy9310/saved_cat2_model/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://Andy9310/saved_cat2_model/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Andy9310/saved_cat2_model/resolve/main/checkpoint-2000/optimizer.bin
457 MB
- Xet hash:
- 75026a0a08edb39e3c6097ad7d0d35af49343238a5b81dc803d1df718bbce93b
- Size of remote file:
- 457 MB
- SHA256:
- 67737e3eb55e7a3178afa834f675adb9cdafa6795958e2d188eb1f1b2102c669
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.