Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
lora
Instructions to use moobastresh/path-to-save-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use moobastresh/path-to-save-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("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("moobastresh/path-to-save-model") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-400/optimizer.bin from moobastresh/path-to-save-model: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/moobastresh/path-to-save-model/resolve/main/checkpoint-400/optimizer.bin
- Command line
-
hf download hf://moobastresh/path-to-save-model/checkpoint-400/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/moobastresh/path-to-save-model/resolve/main/checkpoint-400/optimizer.bin
6.59 MB
- Xet hash:
- b41860582a058623ee919229086bc84afcfdf626e4eda5286d995e8eed099cba
- Size of remote file:
- 6.59 MB
- SHA256:
- ab8736905605d03aa4b7575ee43eb285b404a683c5186733009ddad7339a83e3
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