Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use afbudiman/indobert-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use afbudiman/indobert-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="afbudiman/indobert-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("afbudiman/indobert-classification") model = AutoModelForSequenceClassification.from_pretrained("afbudiman/indobert-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c5e2b60e41119463474804130bb1ee9291c6bb9bd0584cc9864e2abb1163780
- Size of remote file:
- 498 MB
- SHA256:
- ba528341bdb11720881fc843d3c84eefe1b6a31f4e7d7f722ac3b0c3337b2acb
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