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Developing small, task-specific AI models accessible to everyone 🚀

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Here is a list of the task-specific Small Language Models developed by Tanaos for various text processing tasks. Below are the details of each model along with links to their Hugging Face repositories and code examples for easy integration.

Every model can be used and fine-tuned on CPU, making them accessible for a wide range of applications.

Model Size Description Links
Guardrail 0.1B params, 500Mb Flags unsafe, harmful, or off-topic messages. HF • Code Examples
Intent Classification 0.1B params, 500Mb Classifies user messages into predefined intent categories. HF • Code Examples
Reranker 0.1B params, 470Mb Ranks a list of items or search results based on relevance to a query. HF • Code Examples
Sentiment Analysis 0.1B params, 470Mb Determines the sentiment (positive, negative, neutral) of a given text. HF • Code Examples
Emotion Detection 0.1B params, 470Mb Identifies the emotion expressed in a given text. HF • Code Examples
Named Entity Recognition (NER) 0.1B params, 500Mb Detects and classifies named entities in text. HF • Code Examples
Text Anonymization 0.1B params, 500Mb Removes personally identifiable information (PII) from text. HF • Code Examples