

Nasa Smd Ibm St
Overview :
nasa-smd-ibm-st is a sentence embedding model based on Bi-encoder, fine-tuned from the nasa-smd-ibm-v0.1 encoder model. It was trained on 271 million training samples, including 2.6 million domain-specific samples from NASA Science Mission Directorate (SMD) documents. This model aims to enhance natural language technologies, such as information retrieval and intelligent search, for applications in SMD's natural language processing tasks. It can be broadly used in information retrieval, sentence similarity search, and other NASA SMD-related scientific use cases.
Target Users :
Used for natural language processing tasks in the NASA Science Mission Directorate (SMD), enhancing information retrieval and intelligent search performance.
Use Cases
Finding documents or information relevant to a given query.
Matching related questions and answers based on sentence similarity.
Performing intelligent retrieval and analysis of NASA science literature.
Features
Information Retrieval
Sentence Similarity Search
For NASA SMD-related scientific use cases
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