Instructions to use sofia-todeschini/BioLinkBERT-LitCovid-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sofia-todeschini/BioLinkBERT-LitCovid-v1.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sofia-todeschini/BioLinkBERT-LitCovid-v1.0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sofia-todeschini/BioLinkBERT-LitCovid-v1.0") model = AutoModelForSequenceClassification.from_pretrained("sofia-todeschini/BioLinkBERT-LitCovid-v1.0") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -33,7 +33,7 @@ The following hyperparameters were used during training:
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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