Instructions to use csbhr/Vivid-VR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use csbhr/Vivid-VR with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("csbhr/Vivid-VR", 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
Commit History
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Improve model card: Add pipeline tag, library name, license, and update paper/code links
Verified signatureThis PR enhances the model card for the Vivid-VR model by: - Adding `pipeline_tag: image-to-image` to the metadata, which helps users discover the model under relevant categories on the Hugging Face Hub. - Specifying `library_name: diffusers` in the metadata, as the repository is built on `diffusers`, enabling better integration and a "Use in Diffusers" button. - Including `license: apache-2.0` to clearly state the licensing terms of the main repository. - Updating the paper link from "Coming soon!" to the official Hugging Face Papers page (`https://huggingface.co/papers/2508.14483`). - Adding a direct link to the GitHub repository at the top for easier access to the code. - Refactoring the initial title and link section to use cleaner Markdown for improved readability and consistency on the Hugging Face Hub.0f0f75f
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