Image-to-Video
Diffusers
Safetensors
MagiHumanPipeline
text-to-video
image-text-to-video
text-to-audio
text-to-audio-video
image-to-audio-video
image-text-to-audio-video
multimodal
Instructions to use SII-GAIR/daVinci-MagiHuman-Base-1080p with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SII-GAIR/daVinci-MagiHuman-Base-1080p with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SII-GAIR/daVinci-MagiHuman-Base-1080p", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
Upload architecture.png with huggingface_hub
Browse files- .gitattributes +1 -0
- architecture.png +3 -0
.gitattributes
CHANGED
|
@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
text_encoder/tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
text_encoder/tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
| 37 |
+
architecture.png filter=lfs diff=lfs merge=lfs -text
|
architecture.png
ADDED
|
Git LFS Details
|