Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use getrajeev03/debug-example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use getrajeev03/debug-example with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="getrajeev03/debug-example")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("getrajeev03/debug-example") model = AutoModelForSequenceClassification.from_pretrained("getrajeev03/debug-example") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c4b706937b3663e3fcc7a8adc78bd4e014a13f618a24c7c571e6bc43945243e
- Size of remote file:
- 3.9 kB
- SHA256:
- 27f08c8d4e6bfa5034530dabe7e985068946e5e1e9bd20eb0c1d59c67ad81f73
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