Text Classification
Transformers
Safetensors
English
bert
biomedical
clinical
variant-classification
genetics
fine-tuned
text-embeddings-inference
Instructions to use weijiang99/clinvarbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use weijiang99/clinvarbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="weijiang99/clinvarbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("weijiang99/clinvarbert") model = AutoModelForSequenceClassification.from_pretrained("weijiang99/clinvarbert") - Notebooks
- Google Colab
- Kaggle
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README.md
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| Class ID | Label | Description |
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| 1 | **VUS** | Variant of Uncertain Significance |
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| Class ID | Label | Description |
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| 0 | **P/LP** | Pathogenic or Likely Pathogenic |
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| 1 | **VUS** | Variant of Uncertain Significance |
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| 2 | **B/LB** | Benign or Likely Benign |
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