Instructions to use jpodivin/pep_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jpodivin/pep_summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jpodivin/pep_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("jpodivin/pep_summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c20d973209ecb1fb8adf806b54840a37bd5d607e438782671a104c0763bf1b11
- Size of remote file:
- 4.98 kB
- SHA256:
- b90c35f5ffa7b892a1a777c9e17c72115478cb3e1297e312b90bd160a6a74ab2
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