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:
- e51ab8430c3266da6d97886c62d5cde331157e1197c8698997ee7273b23b4ae7
- Size of remote file:
- 892 MB
- SHA256:
- 7c0cb6471e8039ea0affa38ba8dab87ffd737f03cb20aad9ceb605c67fb6ee38
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