Feature Extraction
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
bert
biomedical
lexical semantics
bionlp
biology
science
embedding
entity linking
Instructions to use cambridgeltl/SapBERT-from-PubMedBERT-fulltext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cambridgeltl/SapBERT-from-PubMedBERT-fulltext with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="cambridgeltl/SapBERT-from-PubMedBERT-fulltext")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("cambridgeltl/SapBERT-from-PubMedBERT-fulltext") model = AutoModel.from_pretrained("cambridgeltl/SapBERT-from-PubMedBERT-fulltext", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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