Instructions to use PursuitOfDataScience/t5-large-summary-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PursuitOfDataScience/t5-large-summary-model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PursuitOfDataScience/t5-large-summary-model") model = AutoModelForSeq2SeqLM.from_pretrained("PursuitOfDataScience/t5-large-summary-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59a112f18318b870f916ea178b3cf9ab7da299b70d35951f3c9a2c314317bc8f
- Size of remote file:
- 1.48 GB
- SHA256:
- ce1eade7e186b731208b203c992d170621bcc74fbc63f9adcf929fad03b8a47f
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