Instructions to use dtorber/BioNLP-tech-intro-disc-decoder-tokens-eLife with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-tech-intro-disc-decoder-tokens-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-tech-intro-disc-decoder-tokens-eLife")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-tech-intro-disc-decoder-tokens-eLife") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-tech-intro-disc-decoder-tokens-eLife") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d9a0b2fbffea0282a69bd36687934bf3c77dc982b188da14f9d5d6d0f660ddc
- Size of remote file:
- 648 MB
- SHA256:
- 87c580cf42aec482d9ae38dbfb3386b72d065c6000a49b59519bd9be5b7131e1
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