Text Classification
Transformers
PyTorch
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use HealthNLP/pubmedbert_tlink with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HealthNLP/pubmedbert_tlink with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HealthNLP/pubmedbert_tlink")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HealthNLP/pubmedbert_tlink") model = AutoModelForSequenceClassification.from_pretrained("HealthNLP/pubmedbert_tlink", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
Verified signature- Adding `safetensors` variant of this model (deeb862524818833d35693dd96305c6d9003a1df) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>a727010
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Verified signatureFiles for Jiarui's TLINK classifier with PubMedBert as a starting point, with continued fine tuning on THYME and ChemoTimelines SharedTask data.1272a60 -
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