Instructions to use linxi/tiny-bert-sst2-distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use linxi/tiny-bert-sst2-distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="linxi/tiny-bert-sst2-distilled")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("linxi/tiny-bert-sst2-distilled") model = AutoModelForSequenceClassification.from_pretrained("linxi/tiny-bert-sst2-distilled") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24ae4ea592e92c447041a553334c534eedb9c09fc866849a545bcbcd5ac48c7f
- Size of remote file:
- 17.6 MB
- SHA256:
- 86a3afa70618cffd8f8572bbccb697f32ae63c727d91ff0932894ef73652031a
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