Instructions to use JosephusCheung/ACertainModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JosephusCheung/ACertainModel with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JosephusCheung/ACertainModel", dtype=torch.bfloat16, device_map="cuda") prompt = "masterpiece, best quality, 1girl, brown hair, green eyes, colorful, autumn, cumulonimbus clouds, lighting, blue sky, falling leaves, garden" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Commit ·
4d306b5
1
Parent(s): 9b7e873
Update README.md
Browse files
README.md
CHANGED
|
@@ -19,7 +19,7 @@ widget:
|
|
| 19 |
|
| 20 |
Welcome to ACertainModel - a latent diffusion model for weebs. This model is intended to produce high-quality, highly detailed anime style with just a few prompts. Like other anime-style Stable Diffusion models, it also supports danbooru tags to generate images.
|
| 21 |
|
| 22 |
-
e.g. **
|
| 23 |
|
| 24 |
## 🧨 Diffusers
|
| 25 |
|
|
|
|
| 19 |
|
| 20 |
Welcome to ACertainModel - a latent diffusion model for weebs. This model is intended to produce high-quality, highly detailed anime style with just a few prompts. Like other anime-style Stable Diffusion models, it also supports danbooru tags to generate images.
|
| 21 |
|
| 22 |
+
e.g. **_masterpiece, best quality, 1girl, brown hair, green eyes, colorful, autumn, cumulonimbus clouds, lighting, blue sky, falling leaves, garden_**
|
| 23 |
|
| 24 |
## 🧨 Diffusers
|
| 25 |
|