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
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README.md
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- generated_from_trainer
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metrics:
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- accuracy
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base_model: PubMedBERT
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model-index:
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- name: PubMedBERT-MNLI-MedNLI
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results: []
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- generated_from_trainer
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metrics:
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- accuracy
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base_model: microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext
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model-index:
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- name: PubMedBERT-MNLI-MedNLI
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results: []
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