Instructions to use kailashsp/dreambooth_diffusion_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use kailashsp/dreambooth_diffusion_model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://kailashsp/dreambooth_diffusion_model") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -8,10 +8,14 @@ pipeline_tag: text-to-image
|
|
| 8 |
|
| 9 |
## Model description
|
| 10 |
|
|
|
|
|
|
|
|
|
|
| 11 |
More information needed
|
| 12 |
|
| 13 |
## Intended uses & limitations
|
| 14 |
|
|
|
|
| 15 |
More information needed
|
| 16 |
|
| 17 |
## Training and evaluation data
|
|
|
|
| 8 |
|
| 9 |
## Model description
|
| 10 |
|
| 11 |
+
This is a Stable Diffusion model fine-tuned using Dreambooth on pokemon
|
| 12 |
+
to get cuter pokemons
|
| 13 |
+
|
| 14 |
More information needed
|
| 15 |
|
| 16 |
## Intended uses & limitations
|
| 17 |
|
| 18 |
+
|
| 19 |
More information needed
|
| 20 |
|
| 21 |
## Training and evaluation data
|