Instructions to use nbroad/ynab-pairwise with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nbroad/ynab-pairwise with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nbroad/ynab-pairwise")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nbroad/ynab-pairwise") model = AutoModelForSequenceClassification.from_pretrained("nbroad/ynab-pairwise", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add label2id
Browse files- config.json +4 -0
config.json
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"0": "negative",
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"1": "positive"
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},
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"0": "negative",
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"1": "positive"
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},
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"label2id":{
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"negative": 0,
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"positive": 1
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},
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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