Instructions to use jstep750/animatediff_v2v with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jstep750/animatediff_v2v with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jstep750/animatediff_v2v", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
How to make
- pretrained model: epiCRealism + hyper CFG lora 12steps -> merge with lora weight 0.3
- model merged at step1 + lora model: AnimateLCM_sd15_t2v_lora.safetensors-> merge with lora weight 0.8
# Load the motion adapter
adapter = MotionAdapter.from_pretrained("guoyww/animatediff-motion-adapter-v1-5-3", torch_dtype=torch.float16)
# load SD 1.5 based finetuned model
model_id = "/home/hyejin2/test/models/epiCRealism-hyper-LCM-8.safetensors"
pipe = AnimateDiffVideoToVideoPipeline.from_single_file(model_id, motion_adapter=adapter, torch_dtype=torch.float16)
pipe.save_pretrained("models/hello")
How to use
model_id = "jstep750/animatediff_v2v"
pipe = AnimateDiffVideoToVideoPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
# enable memory savings
pipe.enable_vae_slicing()
pipe.enable_model_cpu_offload()
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