Instructions to use dtorber/BioNLP-intro-disc-decoder-eLife with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-intro-disc-decoder-eLife 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-decoder-eLife")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-intro-disc-decoder-eLife") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-intro-disc-decoder-eLife") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 83e928c7f3157fdf5b629ad69c169bdfdbfb7897672a4b48b8cb5d8f68aba7a9
- Size of remote file:
- 648 MB
- SHA256:
- 4f10f00c785edc50791a97aa6fa51f0c07cacbb4e6d41e625ca2ca5ddfbbd9f3
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