Instructions to use Vidit01/cat-gen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Vidit01/cat-gen with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Vidit01/cat-gen", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Epoch 1
Browse files
logs/train_example/events.out.tfevents.1723023083.e872eb962e47.11176.4
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:543f4dacbb24383076c369d12558461c8e211aece619e1c7c4f1fdc4a81460f7
|
| 3 |
+
size 285640
|
loss_convergence.png
CHANGED
|
|
samples/0001.png
ADDED
|