Instructions to use dtorber/BioNLP-2024-dtorber-baseline_full_attention-eLife with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/BioNLP-2024-dtorber-baseline_full_attention-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-2024-dtorber-baseline_full_attention-eLife")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-2024-dtorber-baseline_full_attention-eLife") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-2024-dtorber-baseline_full_attention-eLife", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e7fb7c449e517a21ba70933d9ccd8b7198ba3bc885c6940bbb479123e7e7742
- Size of remote file:
- 648 MB
- SHA256:
- bc9f3cc1097746570e935ef6d7617a8108c61616df9ff6f30c9580ca294abc7c
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