Instructions to use RobinWZQ/backdoor_KMMD_len_5_a_blond with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RobinWZQ/backdoor_KMMD_len_5_a_blond with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("RobinWZQ/backdoor_KMMD_len_5_a_blond") model = AutoModel.from_pretrained("RobinWZQ/backdoor_KMMD_len_5_a_blond") - Notebooks
- Google Colab
- Kaggle
Improve model card: Add tags, paper, and code links
#1
by nielsr HF Staff - opened
This PR enhances the model card by:
- Adding
pipeline_tag: text-to-imagefor better discoverability. - Adding
library_name: transformersbased onconfig.jsonevidence, enabling the automated 'how to use' widget for thisCLIPTextModelartifact. - Linking to the paper Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models.
- Linking to the GitHub repository: https://github.com/Robin-WZQ/DAA.
- Providing a more informative description of the model based on the research.
Please review and merge if everything looks good!
RobinWZQ changed pull request status to merged