Instructions to use DeepNeural/Pubmed_Summarizer_Model_Trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepNeural/Pubmed_Summarizer_Model_Trained with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("DeepNeural/Pubmed_Summarizer_Model_Trained") model = AutoModelForSeq2SeqLM.from_pretrained("DeepNeural/Pubmed_Summarizer_Model_Trained", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b9640aa88cc434f5a5f4a561262339bdc0765621c241e98ff93b8bab45a8354
- Size of remote file:
- 1.63 GB
- SHA256:
- ea7fdaa2feaeb041e6be438284d748185d17e4304276daa92cddba7cc9a1c1fa
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