Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use pritamdeka/PubMedBERT-MNLI-MedNLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pritamdeka/PubMedBERT-MNLI-MedNLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pritamdeka/PubMedBERT-MNLI-MedNLI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pritamdeka/PubMedBERT-MNLI-MedNLI") model = AutoModelForSequenceClassification.from_pretrained("pritamdeka/PubMedBERT-MNLI-MedNLI") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 21e80f710eed7fa038ee6c5249b622b71da28469f846bf37c7bae379de15648d
- Size of remote file:
- 438 MB
- SHA256:
- 3f968f011daa586c8b88ad58d0f42dc39649575be953a1e2cc062d4f0a4668d5
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