Instructions to use leadingbridge/summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leadingbridge/summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("leadingbridge/summarization") model = AutoModelForSeq2SeqLM.from_pretrained("leadingbridge/summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3930fef827bdd4e53a5e23d1417f9ff861fd062cfd46a28db71589c6f8f1b5c0
- Size of remote file:
- 16.3 MB
- SHA256:
- b5baf8c1abc460afe5e7ca79cf84f74686db46217f874a8fb735f4981e7758ed
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