AI21 Studio's Task-Specific Models offer a range of powerful tools. These models have been specifically designed for their respective tasks and provide high-quality results while optimizing efficiency.
Whether you are an NLP enthusiast or have no prior knowledge, these task-specific models are easy to integrate into your writing platform and provide top-notch results in a matter of minutes. As specialized models, each was optimized for a dedicated purpose, making it significantly more efficient than building it from scratch, and much more cost effective.
Our task-specific models fall into two categories:
- Wordtune models - the brains behind our award-winning applications. Targeting common use-cases for writing and summarizing texts.
- Contextual Answers models - providing accurate and reliable question answering based on specific document(s) context.
The Paraphrase API offers access to a world-class paraphrasing engine that suggests alternative ways to convey the same message using different words. It takes a piece of text and returns a list of paraphrases that convey the same meaning using different words, with the ability to adjust tone and style.
The Grammatical Error Corrections (GEC) API provides access to a top-of-the-line GEC engine that identifies and corrects grammar errors, returning a list of grammar errors and suggestions for corrections.
The Text Improvements API scans a piece of text to see if it can be improved and checks for fluency, clarity, and vocabulary. It returns a list of suggestions if it finds areas that need improvement.
The Summarize API provides access to a world-class summarization engine that generates grounded summaries that remain faithful to the original document. It takes a piece of text or URL and generates summaries that follow the original text flow.
The Text Segmentation API breaks down a piece of text into segments, identifying distinct topics and lines that will work well together and form a coherent piece of text. It supports up to 100,000 characters and can be used to segment long text into smaller chunks and summarize each segment separately.
This Contextual Answers API receives document text, serving as a context, and a question and returns an answer based entirely on this context. This means that if the answer to your question is not in the document, the model will indicate it (instead of providing a false answer).
This Contextual Answers API is the full package: a document Library you can manage and query. This allows users to upload multiple documents to a Library in advance, and then get answers based on these stored documents. The answers will be based solely on this data, and will be backed by the proper context from the organizational knowledge base.
Updated about 2 months ago