Instructions to use a7mid/EnglishSummarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use a7mid/EnglishSummarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("a7mid/EnglishSummarization") model = AutoModelForSeq2SeqLM.from_pretrained("a7mid/EnglishSummarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b27af3f75dc00c2b4d9022a1752eab9e08a8a013336af04434ee00957c25cf2
- Size of remote file:
- 2.28 GB
- SHA256:
- c93ac05e1ed0fa5f4730e090b9c23d48b23e19d427a0330ccad3d97c36c2b39b
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