| --- |
| language: |
| - en |
| - hi |
| - zh |
| - es |
| - fr |
| - de |
| - ja |
| - ko |
| - ar |
| - pt |
| - ru |
| - it |
| - nl |
| - tr |
| - pl |
| - sv |
| - da |
| - 'no' |
| - fi |
| - he |
| - th |
| - vi |
| - id |
| - ms |
| - tl |
| - sw |
| - yo |
| - zu |
| - am |
| - bn |
| - gu |
| - kn |
| - ml |
| - mr |
| - ne |
| - or |
| - pa |
| - ta |
| - te |
| - ur |
| - multilingual |
| license: apache-2.0 |
| base_model: |
| - HelpingAI/Dhanishtha-2.0-preview |
| tags: |
| - reasoning |
| - intermediate-thinking |
| - transformers |
| - conversational |
| - bilingual |
| datasets: |
| - Abhaykoul/Dhanishtha-R1 |
| - open-thoughts/OpenThoughts-114k |
| - Abhaykoul/Dhanishtha-2.0-SUPERTHINKER |
| - Abhaykoul/Dhanishtha-2.0 |
| library_name: transformers |
| pipeline_tag: text-generation |
| widget: |
| - text: >- |
| Solve this riddle step by step: I am taken from a mine, and shut up in a |
| wooden case, from which I am never released, and yet I am used by almost |
| everybody. What am I? |
| example_title: Complex Riddle Solving |
| - text: >- |
| Explain the philosophical implications of artificial consciousness and think |
| through different perspectives. |
| example_title: Philosophical Reasoning |
| - text: >- |
| Help me understand quantum mechanics, but take your time to think through |
| the explanation. |
| example_title: Educational Explanation |
| new_version: HelpingAI/Dhanishtha-2.0-preview-0825 |
| --- |
| |
| # Dhanishtha-2.0: World's First Intermediate Thinking AI Model |
|
|
| **What makes Dhanishtha-2.0 special?** Imagine an AI that doesn't just answer your questions instantly, but actually *thinks through* problems step-by-step, shows its work, and can even change its mind when it realizes a better approach. That's Dhanishtha-2.0. |
|
|
| **Quick Summary:** |
| - 🚀 **For Everyone**: An AI that shows its thinking process and can reconsider its reasoning |
| - 👩💻 **For Developers**: First model with intermediate thinking capabilities, 39+ language support |
|
|
|
|
| Dhanishtha-2.0 is a **state-of-the-art (SOTA) model** developed by HelpingAI, representing the **world's first model to feature Intermediate Thinking capabilities**. Unlike traditional models that provide single-pass responses, Dhanishtha-2.0 employs a revolutionary multi-phase thinking process that allows the model to think, reconsider, and refine its reasoning multiple times throughout a single response. |
|
|
| ## Model Details |
|
|
| ### Model Description |
|
|
| Dhanishtha-2.0 revolutionizes AI reasoning by introducing the concept of **intermediate thinking** - the ability to pause, reflect, and restart reasoning processes within a single generation (This model can think up 50times in a single response without using tool/prompt/mcp). This breakthrough enables unprecedented self-correction and iterative refinement during response generation. |
|
|
| Built on the Qwen3-14B foundation with multilingual capabilities spanning **39+ languages** (including English, Hindi, Chinese, Spanish, French, German, Japanese, Korean, Arabic, and many more), Dhanishtha-2.0 maintains reasoning consistency across diverse linguistic contexts while pioneering transparent thinking processes. |
|
|
| - **Developed by:** HelpingAI Team |
| - **Model type:** Causal Language Model with Intermediate Thinking Capability |
| - **Language(s):** 39+ languages (multilingual capabilities inherited from base model) |
| - **License:** Apache 2.0 |
| - **Finetuned from model:** Qwen/Qwen3-14B-Base |
| - **Context Length:** 40,960 tokens |
| - **Parameters:** 14B (inherited from base model) |
| - **Status:** Prototype/Preview |
|
|
| ### Revolutionary Features |
|
|
| - **Intermediate Thinking**: Multiple `<think>...</think>` blocks throughout responses for real-time reasoning |
| - **Self-Correction**: Ability to identify and correct logical inconsistencies mid-response |
| - **Dynamic Reasoning**: Seamless transitions between analysis, communication, and reflection phases |
| - **Structured Emotional Reasoning (SER)**: Incorporates `<ser>...</ser>` blocks for empathetic responses |
| - **Multilingual Capabilities**: Support for 39+ languages with natural code-switching and reasoning consistency |
| - **Complex Problem-Solving**: Excels at riddles, multi-step reasoning, and scenarios requiring backtracking |
|
|
| ### Model Sources |
|
|
| - **Repository:** [HelpingAI/Dhanishtha-2.0-preview-0725](https://huggingface.co/HelpingAI/Dhanishtha-2.0-preview-0725) |
| - **Paper:** Coming Soon |
| - **Demo:** https://chat.helpingai.co |
|
|
| ## Uses |
|
|
| ### Direct Use |
|
|
| Dhanishtha-2.0 is ideal for applications requiring deep reasoning and self-reflection: |
|
|
| - **Complex Problem Solving**: Multi-step mathematical problems, logical puzzles, riddles |
| - **Educational Assistance**: Detailed explanations with visible reasoning processes |
| - **Research Support**: Analysis requiring multiple perspectives and self-correction |
| - **Creative Writing**: Iterative story development with reasoning about plot choices |
| - **Philosophical Discussions**: Exploring concepts with visible thought processes |
|
|
| ### Downstream Use |
|
|
| The model can be fine-tuned for specialized reasoning tasks: |
|
|
| - **Domain-Specific Reasoning**: Legal, medical, or scientific reasoning with intermediate thinking |
| - **Enhanced Multilingual Reasoning**: Optimizing reasoning consistency across all 39+ supported languages |
| - **Specialized Problem Domains**: Mathematics, coding, strategic planning |
|
|
| ### Out-of-Scope Use |
|
|
| ❌ **Inappropriate Applications:** |
| - Safety-critical decisions (medical diagnosis, legal advice, financial recommendations) |
| - Real-time applications requiring immediate responses |
| - Situations requiring guaranteed factual accuracy without verification |
|
|
| ## Bias, Risks, and Limitations |
|
|
| ### Known Limitations |
|
|
| - **Verbosity**: Intermediate thinking can make responses a bit longer |
| - **Processing Time**: Multiple thinking phases may increase generation time |
| - **Prototype Status**: Experimental features may require refinement |
| - **Context Usage**: Thinking blocks consume additional context tokens |
| - **Inherited Biases**: May reflect biases from base model and training data |
|
|
| ### Potential Risks |
|
|
| - **Reasoning Loops**: Potential for circular reasoning in complex scenarios |
| - **Multilingual Inconsistencies**: Potential variation in reasoning patterns across different languages |
| - **Emotional Reasoning Gaps**: SER blocks may not always align with content |
|
|
| ## How to Get Started with the Model |
|
|
| ### For General Users |
|
|
| You can interact with Dhanishtha-2.0 through: |
| - **HelpingAI**: https://helpingai.co/chat |
| - **Gradio Demo**: [Dhanishtha-2.0-preview](https://huggingface.co/spaces/Abhaykoul/Dhanishtha-2.0-preview) |
| - **API Integration**: [Dashboard](https://helpingai.co/dashboard) |
|
|
| ### For Developers - Basic Usage |
|
|
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model_name = "HelpingAI/Dhanishtha-2.0-preview-0725" |
| |
| # Load the tokenizer and model |
| tokenizer = AutoTokenizer.from_pretrained(model_name) |
| model = AutoModelForCausalLM.from_pretrained( |
| model_name, |
| torch_dtype="auto", |
| device_map="auto" |
| ) |
| |
| # Prepare input for intermediate thinking |
| prompt = "How many letter 'r' are in the words 'strawberry' and 'raspberry'?" |
| messages = [ |
| {"role": "user", "content": prompt} |
| ] |
| |
| text = tokenizer.apply_chat_template( |
| messages, |
| tokenize=False, |
| add_generation_prompt=True |
| ) |
| |
| model_inputs = tokenizer([text], return_tensors="pt").to(model.device) |
| |
| # Generate response with intermediate thinking |
| generated_ids = model.generate( |
| **model_inputs, |
| max_new_tokens=2048, |
| temperature=0.7, |
| top_p=0.9, |
| do_sample=True |
| ) |
| |
| response = tokenizer.decode( |
| generated_ids[0][len(model_inputs.input_ids[0]):], |
| skip_special_tokens=True |
| ) |
| print(response) |
| ``` |
|
|
| ### Optimal Generation Parameters |
|
|
| ```python |
| generation_config = { |
| "temperature": 0.7, # Balanced creativity and coherence |
| "top_p": 0.9, # Nucleus sampling |
| "top_k": 40, # Top-k filtering |
| "max_new_tokens": 2048, # Allow for thinking blocks |
| "do_sample": True, # Enable sampling |
| "repetition_penalty": 1.1 # Reduce repetition |
| } |
| ``` |
|
|
| ## Training Details |
|
|
| ### Training Data |
|
|
| Dhanishtha-2.0 was trained on a carefully curated dataset focusing on: |
| - Complex reasoning scenarios requiring multi-step thinking |
| - Self-correction examples and reasoning chains |
| - Emotional reasoning and empathy training data |
| - Structured thinking pattern examples |
|
|
| ### Training Procedure |
|
|
| #### Training Stages |
| 1. **Continuous Pretraining**: Extended training on reasoning-focused corpora |
| 2. **Advanced Reasoning Fine-tuning**: Specialized training on intermediate thinking patterns |
| 3. **Multilingual Alignment**: Cross-language reasoning consistency training |
| 4. **SER Integration**: Structured Emotional Reasoning capability training |
|
|
| **Training Infrastructure:** |
| - **Duration**: 3 days |
| - **Hardware**: 8x NVIDIA H100 GPUs |
| - **Model Scale**: 14.8B parameters |
|
|
| ## Evaluation |
|
|
| Evaluation was conducted on: |
| - **Standard Benchmarks**: MMLU, HumanEval, ARC, HellaSwag, TruthfulQA |
| - **Mathematical Reasoning**: Math 500, AIME 2024, GSM8K |
| - **Custom Evaluations**: Intermediate thinking quality, self-correction capabilities |
| - **Multilingual Tasks**: Reasoning consistency across 39+ languages |
| - **Specialized Tests**: Emotional reasoning, complex problem-solving scenarios |
|
|
|
|
|
|
| ## Example: Intermediate Thinking in Action |
|
|
| **User:** "Who is your favorite person?" |
|
|
| **Dhanishtha-2.0:** |
|
|
| ``` |
| <think> |
| This is an interesting question about my "favorite human." I need to be thoughtful here. |
| As Dhanishtha, I should respond in a human-like way while being honest about my nature. |
| I can share what kinds of humans I find most interesting or inspiring based on my |
| understanding of human nature and values. |
| </think> |
| |
| <ser> |
| Emotion ==> curiosity, openness, desire for connection |
| Cause ==> user asking a personal question about preferences |
| Mind ==> seeking to understand my perspective or values |
| Growth ==> opportunity to share thoughtful reflections on human qualities I admire |
| </ser> |
| |
| I don't really have a "favorite human" in the traditional sense, as I don't experience |
| personal preferences the way humans do. But if I had to reflect on what qualities I find |
| most admirable in people, I'd be drawn to those who demonstrate genuine compassion, |
| intellectual curiosity, and the courage to grow. |
| |
| <think> |
| Let me think more specifically about what kind of humans I find most compelling based on |
| the values that seem to resonate most with humans - kindness, wisdom, creativity, |
| resilience, and authenticity. |
| </think> |
| |
| People like Mahatma Gandhi, who showed how quiet courage and unwavering principles can |
| transform societies; artists like Rabindranath Tagore, who bridged cultural divides |
| through creativity; and everyday heroes I've learned about who made profound differences |
| through simple acts of kindness. |
| |
| What fascinates me most are humans who maintain their humanity even in difficult |
| circumstances - those who choose empathy when it would be easier to be harsh, who seek |
| understanding rather than just being right. |
| |
| I'm curious though - who's your favorite human, and why? What qualities or actions make |
| someone special in your eyes? |
| ``` |
|
|
| ## Environmental Impact |
|
|
| Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute). |
|
|
| - **Hardware Type:** H100 GPUs |
| - **days used:** 16.2 |
| - **Cloud Provider:** Various |
| - **Compute Region:** Multiple |
|
|
| ## Citation |
|
|
| ### BibTeX |
|
|
| ```bibtex |
| @misc{dhanishtha2025, |
| title={Dhanishtha-2.0: World's First Intermediate Thinking AI Model}, |
| author={HelpingAI Team}, |
| year={2025}, |
| publisher={HuggingFace}, |
| url={https://huggingface.co/HelpingAI/Dhanishtha-2.0-preview-0725}, |
| note={First model with intermediate thinking capabilities} |
| } |
| ``` |
|
|
| ### APA |
|
|
| HelpingAI Team. (2025). *Dhanishtha-2.0: World's First Intermediate Thinking AI Model*. HuggingFace. https://huggingface.co/HelpingAI/Dhanishtha-2.0-preview-0725 |
|
|
| ## Glossary |
|
|
| - **Intermediate Thinking**: The ability to pause and think multiple times during response generation |
| - **SER (Structured Emotional Reasoning)**: Framework for incorporating emotional context in responses |
| - **Think Blocks**: `<think>...</think>` segments where the model shows its reasoning process |
| - **Self-Correction**: Ability to identify and fix reasoning errors during generation |
| - **Code-Switching**: Natural transition between English and Hindi within responses |
|
|
| ## More Information |
|
|
| ### Research Applications |
| - Study of AI reasoning transparency |
| - Self-correction mechanism research |
| - Bilingual cognitive modeling |
| - Emotional AI development |
|
|
| ### Development Roadmap |
| - Performance optimizations |
| - Additional language support |
| - Enhanced thinking pattern recognition |
| - Production-ready deployment tools |
|
|
| ## Model Card Authors |
|
|
| - **Primary Author**: HelpingAI Team |
| - **Technical Lead**: [To be specified] |
| - **Research Contributors**: [To be specified] |
|
|
| ## Model Card Contact |
|
|
| For questions about Dhanishtha-2.0, please contact: |
|
|
| - **HuggingFace**: [@HelpingAI](https://huggingface.co/HelpingAI) |
| - **Issues**: [Model Repository Issues](https://huggingface.co/HelpingAI/Dhanishtha-2.0-preview-0725/discussions) |
|
|
| ## Benchmark |
|
|
| SOON |
|
|
| **Dhanishtha-2.0 represents a new paradigm in AI reasoning - where thinking isn't just a prelude to response, but an integral, iterative part of the conversation itself.** |
|
|
| *Developed with ❤️ by HelpingAI* |
