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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ee4ac966582bf111c229e806a7f76b6c49cd5e17d171d0f4c6a728ff7f805c8f
- Size of remote file:
- 332 kB
- SHA256:
- c9a381941b961c6b5bed96c98f1ad3d4ad018d69f47b5c3c1136b2b05e03fe87
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