Instructions to use poison-attack/t5large-trec_coarse_adv_base64_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use poison-attack/t5large-trec_coarse_adv_base64_1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("poison-attack/t5large-trec_coarse_adv_base64_1") model = AutoModelForSeq2SeqLM.from_pretrained("poison-attack/t5large-trec_coarse_adv_base64_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a74e071d85e755d1f423193fa5ef098bf9348a09f654549fd9b686d9c29bbfc
- Size of remote file:
- 3.13 GB
- SHA256:
- e58d80865f6315b10a0f46ca5764cca085d5c4ab6cad338e49876ea1233cd55f
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