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:
- fe84c5eb7bd8bf8c9f6b9154069d55b83f0d05e99019b3dee1a3defeae069d77
- Size of remote file:
- 5.3 kB
- SHA256:
- 87a98ccf2fd9f221813a3d24845d34c08c726f2d49608500e1dff106edc6dd57
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