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:
- 9e8df0590e67f84b77da5d03113576586b28ac1b85f6d2af8776cc4a1658aab0
- Size of remote file:
- 268 MB
- SHA256:
- 0915b69e76361e60d6e3045a1a646a88a3474ff4de3420a1727a217a789270e9
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