Instructions to use authoranonymous321/mt5_3B-teabreac-AQA_informative with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use authoranonymous321/mt5_3B-teabreac-AQA_informative with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("authoranonymous321/mt5_3B-teabreac-AQA_informative") model = AutoModelForSeq2SeqLM.from_pretrained("authoranonymous321/mt5_3B-teabreac-AQA_informative", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29c0095b107a13e809b3145c8e978423dbc4a08913f806c4c4b26b7048d26949
- Size of remote file:
- 16.3 MB
- SHA256:
- 6a994fd5c500216ec833eec42da2b7a8564e0d78859c468c64557537497d2e63
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