Instructions to use tarudesu/ViHateT5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tarudesu/ViHateT5-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tarudesu/ViHateT5-base") model = AutoModelForSeq2SeqLM.from_pretrained("tarudesu/ViHateT5-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6217f99471f1bcc9b202d04fa632fa408a9c1e27c8fde5a17a0997e110f00b9a
- Size of remote file:
- 892 MB
- SHA256:
- 8b2ffef5c62bd04de09f3bd0f94377fc4f1c2b682c3a04c038180567863e1ceb
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