Instructions to use dtorber/BioNLP-intro-disc-tech-PLOS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-intro-disc-tech-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-intro-disc-tech-PLOS")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-intro-disc-tech-PLOS") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-intro-disc-tech-PLOS") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c642c79bd0c22eee4f730def0d9504c79cffe8ab2b6d9f688890fcd2bb740ef
- Size of remote file:
- 648 MB
- SHA256:
- cbfda255c60b88f5473d1cc9c4f01ec977f940046422fbcc899f639b0eee2e82
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