Instructions to use xkronosx/AutoEncoder-mnist-32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xkronosx/AutoEncoder-mnist-32 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xkronosx/AutoEncoder-mnist-32", 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 7 - step 1000
Browse files- checkpoint.tar +1 -1
- diffusion_pytorch_model.safetensors +1 -1
- samples/sample_38100.png +0 -0
- samples/sample_38200.png +0 -0
- samples/sample_38300.png +0 -0
- samples/sample_38400.png +0 -0
- samples/sample_38500.png +0 -0
checkpoint.tar
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 837628
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:07cd5193a0b186959181e0697785e167ebf8ae82ca1a628afa60621a3bac6ae5
|
| 3 |
size 837628
|
diffusion_pytorch_model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 410260
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:249b12f93cf9bfa3ea500087c5881d72ed1b2721e69434d08117408dd568e404
|
| 3 |
size 410260
|
samples/sample_38100.png
CHANGED
|
|
samples/sample_38200.png
CHANGED
|
|
samples/sample_38300.png
CHANGED
|
|
samples/sample_38400.png
CHANGED
|
|
samples/sample_38500.png
CHANGED
|
|