Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use MonaA/glue_sst_classifier_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MonaA/glue_sst_classifier_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MonaA/glue_sst_classifier_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MonaA/glue_sst_classifier_2") model = AutoModelForSequenceClassification.from_pretrained("MonaA/glue_sst_classifier_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5dd0a64248ca0dcf564d0a8a7039aef9f5a132e0da67192bea9963bc95c63ea
- Size of remote file:
- 433 MB
- SHA256:
- b7efb7f8d7b5b18f1a7b93a46439b11b2f961730a78539d3f0fadcc9a4df7701
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