Instructions to use fateforward/Proteus-ID with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fateforward/Proteus-ID with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fateforward/Proteus-ID", 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
Add metadata and improve model card
#1
by nielsr HF Staff - opened
Hi! I'm Niels, part of the community science team at Hugging Face.
This pull request improves the model card for Proteus-ID by adding relevant metadata:
pipeline_tag: image-to-video: Ensures the model is correctly categorized for users looking for image-to-video generation.library_name: diffusers: The repository structure and file contents (likemodel_index.json) indicate compatibility with thediffuserslibrary.license: apache-2.0: Clarifies the usage terms for the community.
I've also included a brief description of the model's core features—Multimodal Identity Fusion (MIF), Time-Aware Identity Injection (TAII), and Adaptive Motion Learning (AML)—as described in the paper.