Instructions to use VAST-AI/EdenLive-14B-Causal-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VAST-AI/EdenLive-14B-Causal-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("VAST-AI/EdenLive-14B-Causal-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: 895 Bytes
97a8e1a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | # Converted checkpoint layout
The paths in the original notice below refer to the DINOv3 backbone and
projection. In this Diffusers checkpoint, those files are located at:
- `proxy_encoder/model.safetensors` (original `backbone/`)
- `transformer/diffusion_pytorch_model-proxy-projection.safetensors`
(original `projection.safetensors`)
The original notice is retained below.
# NOTICE — vision-encoder
The weights in this directory (`backbone/` and `projection.safetensors`) are DINOv3 by
Meta Platforms, Inc. or derivative works of it made by Vast AI. They are distributed under
the DINOv3 License (see `LICENSE.md` here and in `backbone/`), not under the Apache 2.0
license that covers the rest of this repository. Use must comply with that license,
including its trade-control and prohibited-use terms. Research publications that use these
weights must acknowledge the use of DINOv3.
|