Instructions to use linyq/kiwi-edit-5b-instruct-reference-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use linyq/kiwi-edit-5b-instruct-reference-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("linyq/kiwi-edit-5b-instruct-reference-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
Can some of these be made fp8
#3
by boyetosekuji - opened
it would be great to reduce the VRAM requirements to run on budget GPU's
boyetosekuji changed discussion title from Can some these be made fp8 to Can some of these be made fp8