slim-topics-npu-ov

slim-topics-npu-ov is a specialized function calling model that generates a topic description for a text passage, typically no more than 2-3 words.

This is an OpenVino int4 quantized version of slim-topics, providing a very fast, very small inference implementation, optimized for AI PCs using Intel NPU.

Model Description

• Developed by: llmware
• Model type: tinyllama
• Parameters: 1.1 billion
• Model Parent: llmware/slim-topics
• Language(s) (NLP): English
• License: Apache 2.0
• Uses: Topic categorization and summarization
• RAG Benchmark Accuracy Score: NA
• Quantization: int4

Model Card Contact

llmware on github

llmware on hf

llmware website