Instructions to use dtorber/BioNLP-tech-decoder-PLOS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-tech-decoder-PLOS with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="dtorber/BioNLP-tech-decoder-PLOS")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-tech-decoder-PLOS") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-tech-decoder-PLOS") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5aa19c6bd27e5c9e8fab0b108e69ad6373cdc43c789830d63383024cd92efadf
- Size of remote file:
- 648 MB
- SHA256:
- ab896d50f96222dd0cce6aee272cc8c05516223e937ebd161fdbc0bdbea0c9ba
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