Instructions to use ml4pubmed/albert-base-v2_pub_section with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ml4pubmed/albert-base-v2_pub_section with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ml4pubmed/albert-base-v2_pub_section")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ml4pubmed/albert-base-v2_pub_section") model = AutoModelForSequenceClassification.from_pretrained("ml4pubmed/albert-base-v2_pub_section") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ed5215d5eee0ded299c5550a78ef9bfc7e6ce2fe81d15597640bba698c5d0be
- Size of remote file:
- 46.8 MB
- SHA256:
- 73d166cfbc11189cdb304399363c5dd9c5457b94a1a9c430770f77906946cd2b
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