Instructions to use SnowflakeWang/MV-PBRMat-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SnowflakeWang/MV-PBRMat-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SnowflakeWang/MV-PBRMat-Diffusion", 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
Upload README.md
Browse files
README.md
CHANGED
|
@@ -1,3 +1,10 @@
|
|
| 1 |
-
---
|
| 2 |
-
license: apache-2.0
|
| 3 |
-
--
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
license_link: https://huggingface.co/SnowflakeWang/MV-PBRMat-Diffusion/blob/main/LICENSE
|
| 4 |
+
language:
|
| 5 |
+
- en
|
| 6 |
+
library_name: diffusers
|
| 7 |
+
---
|
| 8 |
+
# Multi-view PBR Material Diffusion Model (MVMat)
|
| 9 |
+
|
| 10 |
+
See https://github.com/Intern-Nexus/MVMat for more details.
|