Text-to-Image
Diffusers
TensorBoard
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use frknayk/dreambooth_training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use frknayk/dreambooth_training with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("frknayk/dreambooth_training", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of sks dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 836 Bytes
b2fe733 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | # What is safetensors ?
[safetensors](https://github.com/huggingface/safetensors) is a different format
from the classic `.bin` which uses Pytorch which uses pickle.
Pickle is notoriously unsafe which allow any malicious file to execute arbitrary code.
The hub itself tries to prevent issues from it, but it's not a silver bullet.
`safetensors` first and foremost goal is to make loading machine learning models *safe*
in the sense that no takeover of your computer can be done.
# Why use safetensors ?
**Safety** can be one reason, if you're attempting to use a not well known model and
you're not sure about the source of the file.
And a secondary reason, is **the speed of loading**. Safetensors can load models much faster
than regular pickle files. If you spend a lot of times switching models, this can be
a huge timesave.
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