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
Model save
Browse files
README.md
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- num_epochs: 5
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- mixed_precision_training: Native AMP
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### Framework versions
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- Transformers 4.35.2
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- num_epochs: 5
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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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- Transformers 4.35.2
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