Instructions to use nlpchallenges/Text-Classification-Synthethic-Dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpchallenges/Text-Classification-Synthethic-Dataset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nlpchallenges/Text-Classification-Synthethic-Dataset")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nlpchallenges/Text-Classification-Synthethic-Dataset") model = AutoModelForSequenceClassification.from_pretrained("nlpchallenges/Text-Classification-Synthethic-Dataset") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48861b6574e5075e96d394befdad926c5042c1019d878371716cb1f7769d3ac7
- Size of remote file:
- 711 MB
- SHA256:
- 292c1982bdfd23c051e284bd00589eb43a7bca931a31e981f814d3ab4246a08b
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