Instructions to use dtorber/BioNLP-intro-disc-tech-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-tech-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-tech-decoder-eLife")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("dtorber/BioNLP-intro-disc-tech-decoder-eLife") model = AutoModelForSeq2SeqLM.from_pretrained("dtorber/BioNLP-intro-disc-tech-decoder-eLife", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0d80ce208bc07ded5e4ecfd2d9106168551f8c1604113d41108d8c38caa747f
- Size of remote file:
- 4.35 kB
- SHA256:
- 506ad298e0daaa9a5f41d28a880d60577783cff741c5a68774b2c8a764d6272d
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