Instructions to use jkefeli/CancerStage_Classifier_T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jkefeli/CancerStage_Classifier_T with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jkefeli/CancerStage_Classifier_T")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jkefeli/CancerStage_Classifier_T") model = AutoModelForSequenceClassification.from_pretrained("jkefeli/CancerStage_Classifier_T", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -7,4 +7,5 @@ tokenizer = AutoTokenizer.from_pretrained("yikuan8/Clinical-BigBird")
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(2) Model type:
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num_classes = 4 #T in [1,2,3,4]
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model = BigBirdForSequenceClassification.from_pretrained(directory, num_labels=num_classes)
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(2) Model type:
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num_classes = 4 #T in [1,2,3,4]
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model = BigBirdForSequenceClassification.from_pretrained(directory, num_labels=num_classes)
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