Instructions to use RobinWZQ/backdoor_KMMD_len_20_a_motor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RobinWZQ/backdoor_KMMD_len_20_a_motor with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("RobinWZQ/backdoor_KMMD_len_20_a_motor") model = AutoModel.from_pretrained("RobinWZQ/backdoor_KMMD_len_20_a_motor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add comprehensive model card for DAA project
#1
by nielsr HF Staff - opened
This PR adds a comprehensive model card for the "Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models" project.
It includes:
- A link to the paper: Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models
- The Apache 2.0 license
- The
transformerslibrary tag, evidenced by theCLIPTextModelarchitecture inconfig.json, for automated code snippets - The
text-to-imagepipeline tag for discoverability on the Hugging Face Hub - A link to the GitHub repository for the code
- An overview of the model and sample usage code directly from the GitHub README
- The BibTeX citation for proper attribution
Please review and merge this PR if everything looks good.
RobinWZQ changed pull request status to merged