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
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}
}
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