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:
- 8aaedd042b7d9342b2879389024360e7e656419aa3a1bb6684b3683c4b2e3d62
- Size of remote file:
- 3.31 kB
- SHA256:
- 89ba671803de91341f41c79751cfa13d8ff4f6eeb6f59f7197a35c93dea44437
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