[docs] update dcvlr readme (#1748)

Author: oelachqar

configs/projects/dcvlr/README.md

@@ -1 +1,73 @@
-WIP
+# DCVLR: Data Curation for Vision Language Reasoning
+
+[![NeurIPS 2025](https://img.shields.io/badge/NeurIPS-2025-blue.svg)](https://neurips.cc/Conferences/2025)
+[![Competition](https://img.shields.io/badge/Competition-Open-green.svg)](https://dcvlr.org)
+
+---
+
+<div align="center">
+
+  <h3>
+   🌐 <a href="https://dcvlr-neurips.github.io">Official webpage</a> •
+   🚀 <a href="https://oumi-ai.typeform.com/to/LnYoisi5">Sign up for updates</a> •
+   🎯 <a href="https://oumi-ai.typeform.com/to/OGPuRt6U">Apply for GPU credits (sponsored by Lambda Labs)</a>
+   </h3>
+</div>
+
+---
+
+
+DCVLR is the first open-data, open-models, open-source competition for data curation in vision-language reasoning, hosted at NeurIPS 2025.
+
+
+## 🎯 Challenge
+
+Participants can leverage any source datasets to curate high-quality instruction-tuning datasets (1K or 10K examples). Participants are encouraged to explore diverse curation strategies, from synthetic data generation to subset selection. Submissions will be evaluated by fine-tuning an undisclosed, open-source vision-language model on the curated data and measuring performance across a wide variety of benchmarks.
+
+## 🚀 Quick Start
+
+Get started with training in minutes:
+
+```bash
+# Install oumi
+uv pip install "oumi[gpu]"
+
+# Train with Molmo-7B-O
+oumi train -c molmo-o --dataset dataset.jsonl
+
+# Train with Qwen2.5-VL-7B-Instruct
+oumi train -c qwen2.5-vl-7b-instruct --dataset dataset.jsonl
+```
+
+## 📅 Key Dates
+
+| Date | Milestone |
+|------|-----------|
+| **June 11, 2025** | Release of Competition Materials |
+| **July 1, 2025** | Submission Portal Opens |
+| **October 1, 2025** | Final Submission Deadline |
+| **November 1, 2025** | Results Announced |
+| **December 2025** | NeurIPS 2025 Presentation |
+
+
+## 📚 Competition Resources
+
+| Resource | Description | Link |
+|----------|-------------|------|
+| 📊 **Starter Kit** | Comprehensive starter kit with example datasets, training scripts, and best practices | [Access Starter Kit](https://huggingface.co/datasets/oumi-ai/dcvlr-starter-kit) |
+| 💻 **Training Scripts** | Starting scripts for fine-tuning multiple vision-language models | [View Scripts](https://github.com/oumi-ai/oumi/tree/main/configs/projects/dcvlr) |
+| 🧪 **Evaluation Code** | Scripts to evaluate model outputs on diverse benchmark development sets | [Get Code](https://github.com/oumi-ai/oumi/tree/main/configs/projects/dcvlr) |
+| ☁️ **Compute Resources** | GPU credits from Lambda Labs for participants | [Apply for Credits](https://oumi-ai.typeform.com/to/OGPuRt6U") |
+| 📚 **Documentation** | Complete guides and tutorials | [View Documentation](https://oumi.ai/docs) |
+
+## 🤝 Sponsors
+
+- **Lambda Labs** - Compute Resources
+- **Oumi.ai** - Competition Support
+
+## 📞 Contact
+
+Have questions? Get in touch with the DCVLR team:
+
+- **Website**: [dcvlr.org](https://dcvlr.org)
+- **Email**: [Contact Form](https://dcvlr.org/contact)