metadata
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