Create README.md

README.md

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+---
+library_name: transformers
+license: apache-2.0
+datasets:
+- Abhaykoul/Dhanishtha-R1
+- open-thoughts/OpenThoughts-114k
+language:
+- en
+base_model:
+- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
+---
+# Dhanishtha Overview
+
+Dhanishtha is a cutting-edge reasoning AI model developed by **HelpingAI**, designed for deep introspection and structured logical analysis. Unlike traditional models that generate immediate responses, Dhanishtha employs a unique **deep-thinking process** process—an internal deliberation phase that enhances reasoning depth before presenting refined answers.
+
+## Model Capabilities
+Dhanishtha operates in **Dhanishtha Mode**, inspired by the **Dhanishtha Nakshatra**, known for wisdom, rhythm, and intellectual depth. The model engages in a multi-step thought process before providing responses, ensuring high accuracy and coherence.
+
+### Key Features:
+- **Structured Internal Reasoning:** Engages in self-dialogue within `<think></think>` tags, iterating through ideas and refining its thought process before responding.
+- **Progressive Thought Refinement:** Evaluates multiple perspectives, making logical connections and ensuring a well-rounded answer.
+- **Emotionally Intelligent Conversational Style:** Responses are expressive, engaging, and tailored for natural human interaction.
+- **Optimized for Critical Thinking & Problem-Solving:** Excels in analytical reasoning, debate, and deep philosophical discussions.
+- **Context Awareness:** Maintains logical coherence in extended interactions, avoiding contradictions and ensuring smooth thought progression.
+
+## Training & Architecture
+- **Model Size:** Optimized for high-performance reasoning with balanced efficiency.
+- **Training Approach:** Fine-tuned using advanced structured learning techniques to enhance deliberative thinking and introspective processing.
+- **Data Sources:** Trained on a diverse dataset covering philosophy, critical reasoning, and problem-solving scenarios to develop a deep intellectual foundation.
+
+## Performance & Benchmarks
+Dhanishtha outperforms conventional models in structured reasoning and contextual depth. The model has been rigorously evaluated across various metrics, demonstrating significant improvements in:
+- **Logical Coherence & Argumentation:** Enhanced ability to follow complex discussions and construct persuasive arguments.
+- **Depth of Analysis:** Excels in breaking down intricate topics into clear, structured responses.
+- **Adaptive Conversational Flow:** Seamlessly shifts between casual and analytical tones based on user input.
+
+## Deployment & Use Cases
+Dhanishtha is designed for:
+- **High-precision academic and philosophical discussions**
+- **Deep problem-solving and strategic reasoning**
+- **Engaging and thought-provoking conversations**
+- **Use in AI-driven research and advanced dialogue systems**
+
+## Benchmarks
+We report Pass@1 accuracy averaged over 16 samples for each problem.
+
+| Model                         | AIME 2024 | MATH 500 | AMC 2023 | Minerva Math | OlympiadBench | Avg. |
+|-------------------------------|-----------|----------|----------|--------------|----------------|------|
+| 2.5-7B-Instruct               | 13.3      | 79.8     | 50.6     | 34.6         | 40.7           | 43.8 |
+| rStar-Math-7B                 | 26.7      | 78.4     | 47.5     | -            | 47.1           | -    |
+| Eurus-2.7B-PRIME              | 26.7      | 79.2     | 57.8     | 38.6         | 42.1           | 48.9 |
+| Qwen2.5-7B-SimpleRL           | 26.7      | 82.4     | 62.5     | 39.7         | 43.3           | 50.9 |
+| DeepSeek-R1-Distill-Qwen-1.5B | 28.8      | 82.8     | 62.9     | 26.5         | 43.3           | 48.9 |
+| Still-1.5B                    | 32.5      | 84.4     | 66.7     | 29.0         | 45.4           | 51.6 |
+| DeepScaleR-1.5B-Preview       | 43.1      | 87.8     | 73.6     | 30.2         | 50.0           | 57.0 |
+| O1-Preview                    | 40.0      | 81.4     | -        | -            | -              | -    |
+| **Dhanishta**                    | 38.2      | 85.1     | 70.3     | 30.5         | 42.0           | 53.2 |
+| **Dhanishta-Large**                    | -      | -    | -     | -         | -           | - |
+
+
+## Credits & License
+Dhanishtha is developed and maintained by **HelpingAI**, pushing the boundaries of AI-driven introspection and structured reasoning. The model is open-source and community-driven, encouraging contributions and collaborative innovation.