Instructions to use Lujia/backdoored_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lujia/backdoored_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Lujia/backdoored_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Lujia/backdoored_bert") model = AutoModel.from_pretrained("Lujia/backdoored_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (26ed58a9c08626ff45292f04659fe7f34acd32ca) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>d0d0cad
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allow flax
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initial commit
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