Instructions to use xiangjx/MuPaD-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xiangjx/MuPaD-512 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xiangjx/MuPaD-512", 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
Fix RNA conditioning, MUSK encoder init, and text/inference mismatch
Browse files
README.md
CHANGED
|
@@ -94,7 +94,7 @@ Generate histopathology images from a text prompt.
|
|
| 94 |
|
| 95 |
```python
|
| 96 |
# Text-to-Image generation
|
| 97 |
-
prompt = "
|
| 98 |
|
| 99 |
output_t2i = pipeline(
|
| 100 |
prompt=prompt,
|
|
|
|
| 94 |
|
| 95 |
```python
|
| 96 |
# Text-to-Image generation
|
| 97 |
+
prompt = "Invasive breast carcinoma with poorly formed glands, hyperchromatic nuclei, and dense fibrous stroma."
|
| 98 |
|
| 99 |
output_t2i = pipeline(
|
| 100 |
prompt=prompt,
|