Text Classification
Transformers
PyTorch
Safetensors
English
bert
document sections
sentence classification
document classification
medical
health
biomedical
text-embeddings-inference
Instructions to use ml4pubmed/scibert-scivocab-uncased_pub_section with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ml4pubmed/scibert-scivocab-uncased_pub_section with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ml4pubmed/scibert-scivocab-uncased_pub_section")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ml4pubmed/scibert-scivocab-uncased_pub_section") model = AutoModelForSequenceClassification.from_pretrained("ml4pubmed/scibert-scivocab-uncased_pub_section") - Notebooks
- Google Colab
- Kaggle
Commit ·
fad04af
1
Parent(s): ba7656f
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (9312295f0e10f698797e678e77e57e875cd10acd)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
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