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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 82 Bytes
86042c0 | 1 2 3 4 5 6 7 8 | {
"[CLS]": 101,
"[MASK]": 103,
"[PAD]": 0,
"[SEP]": 102,
"[UNK]": 100
}
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