Instructions to use Narsil/tiny-distilbert-sequence-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Narsil/tiny-distilbert-sequence-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Narsil/tiny-distilbert-sequence-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Narsil/tiny-distilbert-sequence-classification") model = AutoModelForSequenceClassification.from_pretrained("Narsil/tiny-distilbert-sequence-classification") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7456ff6b579fadacbc19ff535849024ee722a40b38b73ae0defea4d2bd615ec6
- Size of remote file:
- 251 kB
- SHA256:
- c3ada16859a7d5076787f305df1b779a277353c822d4740a0b4e962614a9c74e
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