Dhanishtha-2.0-RKllm

Dhanishtha-2.0

Dhanishtha-2.0 Highlights

Dhanishtha-2.0 is a groundbreaking reasoning AI model developed by HelpingAI, representing the 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.

• World's First Intermediate Thinking Model: Uniquely capable of multiple thinking phases throughout a single response, enabling deeper analysis and self-correction during generation.
• Dynamic Reasoning: Seamlessly integrates <think>...</think> blocks at any point in the response, allowing for real-time problem decomposition and iterative refinement.
• Enhanced Problem-Solving Architecture: Excels at complex riddles, multi-step reasoning, and scenarios requiring backtracking and re-evaluation of initial assumptions.
• Structured Emotional Intelligence: Incorporates SER (Structured Emotional Reasoning) with <ser>...</ser> blocks for empathetic and contextually aware responses.
• Bilingual Reasoning Capabilities: Native support for English and Hindi with natural code-switching between languages.

Model Overview

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 breakthrough enables the model to:

• Type: Causal Language Model with Intermediate Thinking Capability
• Training Stage: Continuous Pretraining and Advanced Reasoning Fine-tuning.
• Base model: Qwen/Qwen3-14B-Base
• Thinking Mode: Multiple <think>...</think> blocks per response
• Context Length: 40,960 tokens natively
• Reasoning Depth: Multi-layered with self-correction mechanisms

Revolutionary Intermediate Thinking

Unlike traditional models that engage in single-phase reasoning, Dhanishtha-2.0 introduces Intermediate Thinking - the ability to pause, reflect, and reconsider throughout the response generation process. This breakthrough allows the model to:

• Think Multiple Times: Insert reasoning blocks at any point during response generation
• Self-Correct in Real-Time: Identify and correct logical inconsistencies mid-response
• Explore Alternative Perspectives: Consider multiple approaches before settling on conclusions
• Demonstrate Uncertainty: Express doubt and reconsider initial assumptions naturally

Key Features

1 Intermediate Thinking

Unlike traditional models that think once before responding, Dhanishtha-2.0 can engage in multiple thinking sessions throughout its response, allowing for:

• Self-correction when initial reasoning seems flawed
• Alternative exploration of different solution paths
• Iterative refinement of ideas and conclusions
• Natural hesitation and reconsideration patterns

2 Dynamic Reasoning Flow

The model seamlessly transitions between:

• Analysis phases (<think> blocks) for internal reasoning
• Communication phases for sharing insights with users
• Reflection phases for questioning previous assumptions
• Synthesis phases for bringing ideas together

3. Structured Emotional Reasoning (SER)

<ser>
Emotion ==> frustration, curiosity
Cause ==> complex problem, initial confusion  
Mind ==> analytical, determined
Growth ==> patience, systematic approach
</ser>

Quickstart

The following code demonstrates how to use Dhanishtha-2.0 with its unique intermediate thinking capabilities:

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "HelpingAI/Dhanishtha-2.0-preview"

# 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 with thinking enabled
prompt = "Who is your favorite person"
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)

Intermediate Thinking in Action

What makes Dhanishtha-2.0 unique is its ability to think multiple times throughout a response. Here's an example:

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?

Best Practices

Optimal Generation Parameters

generation_config = {
    "temperature": 0.7,
    "top_p": 0.9,
    "top_k": 40,
    "max_new_tokens": 2048,
    "do_sample": True
}

Effective Prompting

• Encourage exploration: "Think through this step by step and reconsider if needed"
• Allow uncertainty: "Take your time to work through different possibilities"
• Request thinking: "Show your reasoning process as you work through this"

License & Usage

This model is released under the Apache 2.0 License. It is designed for research and educational purposes, with commercial applications welcome under the license terms.

Prototype Status

[!NOTE] Dhanishtha-2.0 is currently a prototype model representing the first implementation of Intermediate Thinking technology. While demonstrating groundbreaking capabilities, users should expect:

• Experimental features that may require refinement
• Potential verbosity due to multiple thinking phases
• Ongoing development and optimization

Citation

If you use Dhanishtha-2.0 in your research, please cite:

@misc{dhanishtha2025,
  title={Dhanishtha-2.0: First Model with Intermediate Thinking Capabilities},
  author={HelpingAI Team},
  year={2025},
  publisher={HuggingFace},
  url={https://huggingface.co/HelpingAI/Dhanishtha-2.0}
}

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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