Instructions to use hetpandya/t5-base-tapaco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hetpandya/t5-base-tapaco with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hetpandya/t5-base-tapaco") model = AutoModelForSeq2SeqLM.from_pretrained("hetpandya/t5-base-tapaco", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24ab24300ff3241da32c134834474c64c565e26ed801addbd2aeda47f763cf26
- Size of remote file:
- 3.12 kB
- SHA256:
- 72d49a8ebf10e3ccfbc161761804a4dbc720fb5e6bab320c1f2a3b1bf23c1614
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