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:
- 2c70dadf9a2425d36b4bcabe0a52fc4822d2136792f0f682dbcade6c69228630
- Size of remote file:
- 3.38 kB
- SHA256:
- 8ab6ae881fab3cf4b233bb4f4dcf88116bb87b0c7c3f589b0f1144e459932a1e
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