Instructions to use serpapi/bert-base-local-results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use serpapi/bert-base-local-results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="serpapi/bert-base-local-results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("serpapi/bert-base-local-results") model = AutoModelForSequenceClassification.from_pretrained("serpapi/bert-base-local-results") - Notebooks
- Google Colab
- Kaggle
Commit ·
87e43f0
1
Parent(s): fd364ca
Update label_mapping.json to Huggingface standard
Browse files- label_mapping.json +13 -1
label_mapping.json
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{
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"1": "rating",
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"2": "type",
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"3": "years in business",
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"4": "service options",
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"5": "hours",
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"6": "reviews",
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"7": "address",
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"8": "description",
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"9": "price",
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"10": "button text",
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"11": "phone"
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}
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