Update README.md

README.md

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 ## About
-The Odia Generative AI (in short, OdiaGenAI) is an initiative to research Generative AI and Large Language Models (LLMs) for the low-resource Odia language.
+OdiaGenAI is an open research initiative advancing Generative AI, LLMs, and multimodal technologies for Odia and low-resource Indic languages through community-driven, open-source collaboration.
 
-## Objective
-The OdiaGenAI aims to 
-1. Build pre-trained Odia LLM, 
-2. Fine-tuned Odia LLM, and 
-3. Instruct LLM (Odia). 
+---
+
+## Vision
+Empowering Odia and low-resource Indic languages through open, multimodal, and community-owned AI.
+
+---
+
+## Related Hugging Face Organizations
+
+OdiaGenAI collaborates with and maintains close ties to other HF organizations that focus on Odia and Indic LLMs:
+
+* **🔗 [OdiaGenAI](https://huggingface.co/OdiaGenAI)** – Main org for Odia datasets, models, and AI tools (text, speech, OCR, multimodal). :contentReference[oaicite:2]{index=2}
+* **🔗 [OdiaGenAI-LLM](https://huggingface.co/OdiaGenAI-LLM)** – Focused LLM org with additional Odia and Indic-centric model releases (Mistral, LLaMA, instruction sets). :contentReference[oaicite:3]{index=3}
+* **🔗 [OdiaGenAIdata](https://huggingface.co/OdiaGenAIdata)** – Dataset-centric org hosting large corpora for Odia pretraining and evaluation (if separate).  
+
+
+## Objectives
+OdiaGenAI focuses on:
+
+- **Foundation Models for Odia and Indic Languages**
+- **Instruction-tuned and Task-specific LLMs for Indic Use Cases**
+- **Speech and OCR Technologies for Odia and Indic Languages**
+- **Multimodal AI (Text + Vision + Speech) for Low-resource Languages**
+- **Open Data Creation, Benchmarks, and Evaluation Frameworks**
 
-The data, code, and models will be available to the public for research and non-commercial purposes.  
 
-## Why OdiaGenAI
+All outputs are released for **research and non-commercial use**.
 
-* **First**: Though many LLMs support multilingual, including Odia language, the performance for various tasks (e.g., content generation, question-answering) is limited due to the amount of ingested data for Odia. 
-* **Second**: There are subscriptions or fees associated with the high-performing LLMs.
+---
+
+## Why OdiaGenAI?
+
+* **Low-resource challenge** — Odia support in existing LLMs is limited due to scarce training data.
+* **Openness** — Proprietary models restrict access; we provide free, open models and datasets.
+* **Ethics & privacy** — Transparent data practices and community ownership of language tech.
+
+---
 
-* **Third**: The usage (privacy) and bias of data input to these LLMs are in question.
+## Focus Research Areas
 
-## What are the focus research areas of OdiaGenAI
-We have divided the primary focus areas into three parts.
+### 1. Literature & Benchmarking
+Survey and evaluate generative AI and multimodal models for Odia.
 
-**1. Literature Survey:** Investigate the latest developments in Generative AI and LLMs and analyze current methods to support the Odia language for different tasks. 
+### 2. Development
+Curate datasets; build tokenizers, models, and training pipelines.
 
-**2. Development:** Developing pre-trained and fine-tuned Odia LLM, which includes dataset preparation, model training, evaluation, prompt engineering, and API development. 
+### 3. Deployment & Access
+Host models and tools via **Hugging Face**, along with APIs and demos.
 
-**3. Deployment:** Deploy the Odia LLM models for public access for research and non-commercial purposes.
+---
+
+## Who Can Use OdiaGenAI?
+* Researchers, students, developers, and NGOs.  
+Models and datasets are available via **Hugging Face for research and non-commercial purposes**. Contact us for special use cases.
 
-## Who can use OdiaGenAI LLMs
-The models (pre-trained/fine-tuned) will be available through Hugging Face for research and non-commercial purposes. Feel free to contact us for a domain-specific application or particular use cases. 
+---
 
-## What are the use cases of OdiaGenAI LLMs
-There are several use cases of OdiaGenAI LLMs. Three primary domains relating to Odisha which we are focusing to use the developed LLM are:
+## Key Application Areas
 * Education
 * Healthcare
-* Governance
-* Tourism
-* Agriculture
-* Industrial Application
+* Governance*
+
 
 ## Contributors
 * [Shantipriya Parida (Founder)](https://www.linkedin.com/in/shantipriya-parida-9781a9127/)
 * [Sambit Sekhar (Founder)](https://www.linkedin.com/in/sambit-sekhar-ai/)
-* [Soumendra Kumar Sahoo](https://www.linkedin.com/in/soumendrak/)
 * [Swateek Jena](https://www.linkedin.com/in/swateek/)
 * [Abhijeet Parida](https://www.linkedin.com/in/a-parida/)
 * [Dr. Satya Ranjan Dash](https://ksca.kiit.ac.in/profiles/satya-ranjan-dash/)
-* [Guneet Singh Kohli](https://www.linkedin.com/in/guneetsk99/)
+
 
   *About our logo:* The critically endangered [Olive Ridley](https://roundglasssustain.com/photostories/olive-ridley-turtles-endangered) sea turtle is the world's smallest and most prevalent marine turtle. Travel thousands of kilometers in the ocean for nesting. The Gahirmatha Marine Sanctuary in [Odisha](https://en.wikipedia.org/wiki/Odisha) is the largest known mass nesting rookery for olive ridley sea turtles worldwide.
 
@@ -63,7 +89,7 @@ If you find this repository useful, please consider giving 👏 and citing:
 
 ```
 @misc{OdiaGenAI,
-  author = {Shantipriya Parida and Sambit Sekhar and Soumendra Kumar Sahoo and Swateek Jena and Abhijeet Parida and Satya Ranjan Dash and Guneet Singh Kohli},
+  author = {Shantipriya Parida and Sambit Sekhar and Swateek Jena and Abhijeet Parida and Satya Ranjan Dash},
   title = {OdiaGenAI: Generative AI and LLM Initiative for the Odia Language},
   year = {2023},
   publisher = {Hugging Face},