Instructions to use Mademon/Centa_I2V-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Mademon/Centa_I2V-lora 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("ai-toolkit/Wan2.2-I2V-A14B-Diffusers-bf16", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Mademon/Centa_I2V-lora") prompt = "A man with short gray hair plays a red electric guitar." input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png") image = pipe(image=input_image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Upload Centa_I2V_000001750_low_noise.safetensors with huggingface_hub
Browse files
Centa_I2V_000001750_low_noise.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7b32f6b71ad76323bebf191f88e08c93542e0523ab6918db4fb7a9d8c7d6aae1
|
| 3 |
+
size 306808360
|