Instructions to use sgugger/tiny-distilbert-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgugger/tiny-distilbert-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sgugger/tiny-distilbert-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sgugger/tiny-distilbert-classification") model = AutoModelForSequenceClassification.from_pretrained("sgugger/tiny-distilbert-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ffbc2755493ee0c761e60bc9614fccd6daa9e8df4e9ea65bae4787d613cfb0f
- Size of remote file:
- 310 kB
- SHA256:
- a038e8b517cac9bdd1519c81a56d82e52af303198dfe30b68e3946a7cf6ee6e6
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