Instructions to use WaveCut/Cosmos3-Super-Text2Image-Quanto-FP8-Transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Cosmos3-Super-Text2Image-Quanto-FP8-Transformer with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/Cosmos3-Super-Text2Image-Quanto-FP8-Transformer", 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 Settings
- Draw Things
- DiffusionBee
Update README.md
Browse files
README.md
CHANGED
|
@@ -17,7 +17,7 @@ license_link: https://openmdw.ai/license/1-1/
|
|
| 17 |
|
| 18 |
This repository contains a transformer-only FP8/float8 Quanto quantization for [nvidia/Cosmos3-Super-Text2Image](https://huggingface.co/nvidia/Cosmos3-Super-Text2Image).
|
| 19 |
|
| 20 |
-
|
| 21 |
[nvidia/Cosmos3-Super-Text2Image](https://huggingface.co/nvidia/Cosmos3-Super-Text2Image).
|
| 22 |
|
| 23 |
Only `transformer/` is provided as a weight artifact. The VAE, scheduler, tokenizers, safety checker, and other components are loaded from the base model.
|
|
|
|
| 17 |
|
| 18 |
This repository contains a transformer-only FP8/float8 Quanto quantization for [nvidia/Cosmos3-Super-Text2Image](https://huggingface.co/nvidia/Cosmos3-Super-Text2Image).
|
| 19 |
|
| 20 |
+
Read NVIDIA's card, license, safety notes, and prompt-format guidance here:
|
| 21 |
[nvidia/Cosmos3-Super-Text2Image](https://huggingface.co/nvidia/Cosmos3-Super-Text2Image).
|
| 22 |
|
| 23 |
Only `transformer/` is provided as a weight artifact. The VAE, scheduler, tokenizers, safety checker, and other components are loaded from the base model.
|