Instructions to use drmeeseeks/dreambooth_diffusion_model-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use drmeeseeks/dreambooth_diffusion_model-v2 with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://drmeeseeks/dreambooth_diffusion_model-v2") - Notebooks
- Google Colab
- Kaggle
Download inf3.png from drmeeseeks/dreambooth_diffusion_model-v2: direct link, hf CLI and curl.
- Browser
- Download file 1.14 MB
-
https://huggingface.co/drmeeseeks/dreambooth_diffusion_model-v2/resolve/main/inf3.png
- Command line
-
hf download hf://drmeeseeks/dreambooth_diffusion_model-v2/inf3.png
-
curl -L -o inf3.png https://huggingface.co/drmeeseeks/dreambooth_diffusion_model-v2/resolve/main/inf3.png
1.14 MB

- Xet hash:
- af926cdc3d2bc150545fbac73216a02207f023d0d56687bd6a6f6a61835a4067
- Size of remote file:
- 1.14 MB
- SHA256:
- 0ef89f30e406c9467ba4851b25007418030cbb51b36fbb1f96c69bdec3ed1deb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.