Instructions to use CompVis/ldm-text2im-large-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CompVis/ldm-text2im-large-256 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256", 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
- Local Apps
- Draw Things
- DiffusionBee
Update model_index.json
Browse files- model_index.json +1 -1
model_index.json
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
{
|
| 2 |
-
"_class_name": "
|
| 3 |
"_diffusers_version": "0.0.4",
|
| 4 |
"bert": [
|
| 5 |
"latent_diffusion",
|
|
|
|
| 1 |
{
|
| 2 |
+
"_class_name": "LDMTextToImagePipeline",
|
| 3 |
"_diffusers_version": "0.0.4",
|
| 4 |
"bert": [
|
| 5 |
"latent_diffusion",
|