Instructions to use sana-ngu/HaT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sana-ngu/HaT5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sana-ngu/HaT5") model = AutoModelForSeq2SeqLM.from_pretrained("sana-ngu/HaT5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d62fbb49a97604b59400498a35fec74ba739498a2bcd754f5a02caec283bbbe7
- Size of remote file:
- 892 MB
- SHA256:
- 205a7254c80c856a4e5185621b604cebce8e534c8a196c296e9e4601e942f902
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