README.md

---
license: apache-2.0
inference: false 
tags: [green, p1, llmware-fx, ov, emerald]
---

# slim-extract-tiny-ov  

**slim-extract-tiny-ov** is a specialized function calling model with a single mission to look for values in a text, based on an "extract" key that is passed as a parameter.  No other instructions are required except to pass the context passage, and the target key, e.g., 

  text_passage = "The company announced that for the current quarter the total revenue increased by 9% to $125 million."

  llm_response = model.function_call(text_passage, function="extract", params=["revenue"])

  Output: `llm_response = {"revenue": [$125 million"]}`
  

This is an OpenVino int4 quantized version of slim-extract-tiny, 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-extract-tiny
- **Language(s) (NLP):** English  
- **License:** Apache 2.0  
- **Uses:** Extraction of values from complex business documents    
- **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)