Instructions to use Disty0/Index-anisora-5B-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Disty0/Index-anisora-5B-diffusers 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("Disty0/Index-anisora-5B-diffusers", 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
File size: 525 Bytes
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license: apache-2.0
base_model:
- IndexTeam/Index-anisora
pipeline_tag: image-to-video
library_name: diffusers
---
Diffusers version of [IndexTeam/Index-anisora 5B](https://huggingface.co/IndexTeam/Index-anisora)
Source file: https://huggingface.co/IndexTeam/Index-anisora/blob/main/5B/1000/mp_rank_00_model_states.pt
Soruce file sha256sum: `5ebdea887b5eda837aabcbf3ed9a344bd518e9b8114829a4b195daf289a6d775`
Text Encoder and VAE are from [THUDM/CogVideoX-5b-I2V](https://huggingface.co/THUDM/CogVideoX-5b-I2V)
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