Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Rami/multi-label-class-classification-on-github-issues with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rami/multi-label-class-classification-on-github-issues with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Rami/multi-label-class-classification-on-github-issues")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Rami/multi-label-class-classification-on-github-issues") model = AutoModelForSequenceClassification.from_pretrained("Rami/multi-label-class-classification-on-github-issues") - Inference
- Notebooks
- Google Colab
- Kaggle
Ctrl+K
- Dec01_02-11-09_fab31162c3c4
- Dec01_02-33-04_9e50f2f8301e
- Jan07_17-42-14_79e5d04155a9
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- Jan07_17-49-41_79e5d04155a9
- Jan08_19-21-52_50cc6bd24d93
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- Jan08_19-47-31_50cc6bd24d93
- Jan08_19-47-53_50cc6bd24d93
- Jan11_00-19-28_4053820fab0a
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- Jan11_00-26-14_4053820fab0a
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- Jan11_00-49-43_4053820fab0a
- Jan11_03-30-01_dec631e02d2a
- Jan11_03-37-54_dec631e02d2a