---
license: apache-2.0
inference: false 
base_model: llmware/slim-q-gen
base_model_relation: quantized 
tags: [green, p1, llmware-fx, ov, emerald]
---

# slim-q-gen-tiny-ov  

**slim-q-gen-tiny-ov** is a specialized function calling model that implements a generative 'question' (e.g., 'q-gen') function, which takes a context passage as an input, and then generates as an output a python dictionary consisting of one key:

 `{'question': ['What was the amount of revenue in the quarter?']} `  

The model has been designed to accept one of three different parameters to guide the type of question-answer created: 'question' (generates a standard question), 'boolean' (generates a 'yes-no' question), and 'multiple choice' (generates a multiple choice question).

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


### Model Description

- **Developed by:** llmware  
- **Model type:** tinyllama  
- **Parameters:** 1.1 billion
- **Model Parent:** llmware/slim-q-gen
- **Language(s) (NLP):** English  
- **License:** Apache 2.0  
- **Uses:** Question generation from a context passage     
- **RAG Benchmark Accuracy Score:** NA  
- **Quantization:** int4  

## Model Card Contact

[llmware on github](https://www.github.com/llmware-ai/llmware)  

[llmware on hf](https://www.huggingface.co/llmware)  

[llmware website](https://www.llmware.ai)