Instructions to use bdsqlsz/framepack_oneframe_qinglong_figure with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bdsqlsz/framepack_oneframe_qinglong_figure with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lllyasviel/FramePackI2V_HY", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("bdsqlsz/framepack_oneframe_qinglong_figure") prompt = "-" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
qinglong_figure

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Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Useage
Default prompts:"transform character to PVC figure with simple background."
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Model tree for bdsqlsz/framepack_oneframe_qinglong_figure
Base model
lllyasviel/FramePackI2V_HY