Instructions to use dtorber/BioNLP-tech-intro-disc-PLOS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-tech-intro-disc-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-intro-disc-PLOS")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-tech-intro-disc-PLOS") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-tech-intro-disc-PLOS") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f5cbb08da9c1b32126e08bfb5a57780df70170be2cd3de559c07caf41d779f6
- Size of remote file:
- 648 MB
- SHA256:
- be0c1d57041d488fb101cb7316f3477bfe418fbc6db4f3e40db7afea82a5c30f
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