Instructions to use dejanseo/Intent-XS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dejanseo/Intent-XS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dejanseo/Intent-XS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dejanseo/Intent-XS") model = AutoModelForSequenceClassification.from_pretrained("dejanseo/Intent-XS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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The model is designed to be deployed in an automated pipeline capable of classifying search query intent for thousands (or even millions) of search queries from common data sources such as Google Search Console, SEMRush, Ahrefs, Moz, Majestic and Google Ads.
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This is a
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# Engage Our Team
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Interested in using this in an automated pipeline for bulk query processing?
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The model is designed to be deployed in an automated pipeline capable of classifying search query intent for thousands (or even millions) of search queries from common data sources such as Google Search Console, SEMRush, Ahrefs, Moz, Majestic and Google Ads.
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This is a demo model which may occasionally misclassify some queries. In a typical commercial project, a larger model is deployed for the task, and in special cases, a domain-specific model is developed for the client.
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# Engage Our Team
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Interested in using this in an automated pipeline for bulk query processing?
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