Merge pull request #27 from fabiomatricardi/main

Update README.md

Author: DimaPastushenkov

README.md

@@ -51,6 +51,10 @@ MANIPULATION PROGRAM)
 * [Stable Diffusion 2.1 on Intel ARC](https://github.com/jfsunx/OVSD21) - A simple and easy-to-use demo to run Stable Diffusion 2.1 for Intel ARC graphics card based on OpenVINO.
 * [AI Video Builder](https://github.com/jediknight813/ai_video_builder) - Make videos with AI images from YouTube videos.
 * [LocalAI](https://github.com/mudler/LocalAI) - LocalAI is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that’s compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing.
+* [AI structured data Extraction](https://github.com/fabiomatricardi/NuExtract-1.5-openvino) - A streamlit interface with NuExtract-1.5-tiny and openvino-genai to extract data from plain text into structured custom json formats. The Repo also gives a small tutorial on how to convert NuExtract-1.5-tiny into OpenVINO IR format.
+* [StableLM-3B Chatbot](https://github.com/fabiomatricardi/OpenVINO-StableLM-3B-streamlit) - A streamlit CHATBOT interface with stablelm-zephyr-3b quantized in 4bit and optimum-intel. The Interface has a kind text streaming effect, and the number of turns are handled to not exceed the context window. The Model used is published on Hugging Face Hub and was created with the free HF Space hosting the [NCCF-quantization tool](https://huggingface.co/spaces/OpenVINO/nncf-quantization).
+* [Gemma2-2b AI Chat App](https://github.com/fabiomatricardi/OpenVINO-Gemma2B-streamlit) - A beautiful Chat Interface, with interactive tuning parameters, powered by Optimum-Intel[openvino], Streamlit and the small but powerful Gemma2-2b-instruct model by Google. The model is an int4 quantized version, hosted on Hugging Face Hub.
+* [LaMini Power](https://github.com/fabiomatricardi/openvino-Lamini) - An experimental text based chat interface in the terminal running the [LaMini-Flan-T5-248M](https://github.com/mbzuai-nlp/lamini-lm/) . This is a breakthrough made possible by openvino, because encoder-decoder model could not be quantized. The LaMini model family is a highly curated herd of very small models achieving strong accuracy even with only 512 tokens of context length.
 
 
 ### AI Computer Vision