Instructions to use jkefeli/CancerStage_Classifier_N with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jkefeli/CancerStage_Classifier_N with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jkefeli/CancerStage_Classifier_N")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jkefeli/CancerStage_Classifier_N") model = AutoModelForSequenceClassification.from_pretrained("jkefeli/CancerStage_Classifier_N", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 299 Bytes
1e77f09 b7d24fc 663ea13 890ad58 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | To use the model, add the following from the transformers package:
(1) Tokenizer:
tokenizer = AutoTokenizer.from_pretrained("yikuan8/Clinical-BigBird")
(2) Model type:
#N in [0,1,2,3]
num_classes = 4
model = BigBirdForSequenceClassification.from_pretrained(directory, num_labels=num_classes) |