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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6fa5bd138fa2e736e145fe7f071369eb88419c65fb30ce4a1aa002b870c53d9b
- Size of remote file:
- 2.14 MB
- SHA256:
- 4276a1eee28f57f1fe9c3be872d73ed33558801c04009a1e6f52cf7bd6dfdee6
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