Instructions to use moshew/mpnet-base-sst2-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moshew/mpnet-base-sst2-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="moshew/mpnet-base-sst2-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("moshew/mpnet-base-sst2-distilled") model = AutoModelForSequenceClassification.from_pretrained("moshew/mpnet-base-sst2-distilled") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
{'test_accuracy': 0.9426605504587156, 'test_loss': 0.1693699210882187, 'test_runtime': 1.7713, 'test_samples_per_second': 492.29, 'test_steps_per_second': 3.952}
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