---
license: apache-2.0
base_model: Qwen/Qwen3-1.7B
tags:
- qwen3
- fine-tuned
- hito
- hitonet
- reasoning
- conversational
- thinking
- adaptive-reasoning
- tree-of-thought
- hierarchical-reasoning
- cognitive-framework
- self-aware-ai
- anti-hallucination
- synthetic-data
- gguf
- llama-cpp
- ollama
pipeline_tag: text-generation
language:
- en
library_name: transformers
---

<div align="center">

<img src="https://hitonet.com/assets/img/hitonet-logo-dark.png" alt="Hitonet" height="60"/>

<img src="meet_hito.png" alt="Meet Hito" width="400"/>

# Hito 1.7B

### Brain, Heart, and a Really Good Memory

[![GGUF Downloads](https://img.shields.io/badge/GGUF_for_Ollama/llama.cpp-ff6b35?style=for-the-badge&logo=meta&logoColor=white)](https://huggingface.co/hitonet/hito-1.7b-GGUF)

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---

<img src="https://img.shields.io/badge/Status-Production-22c55e?style=flat-square" alt="Status"/>
<img src="https://img.shields.io/badge/Parameters-1.7B-blue?style=flat-square" alt="Parameters"/>
<img src="https://img.shields.io/badge/Context-32K-green?style=flat-square" alt="Context"/>
<img src="https://img.shields.io/badge/License-Apache_2.0-red?style=flat-square" alt="License"/>

<img src="https://img.shields.io/badge/Model_Weights-Apache_2.0_(Open)-green?style=flat-square" alt="Model License"/>
<img src="https://img.shields.io/badge/NCR_Method-CC_BY--NC--ND_(Commercial_License_Required)-red?style=flat-square" alt="Method License"/>

</div>

---

## 🧠 Cognitive Bias Resistance

Hito is specifically trained to resist cognitive biases that trip up most AI models and humans alike.

### The Bat and Ball Test

> *"A bat and a ball cost $1.10 together. The bat costs $1.00 more than the ball. How much does the ball cost?"*

Most people (and AI models) instinctively say **10 cents**. That's wrong.

| Model | Parameters | Answer | Correct |
|-------|------------|--------|---------|
| **Hito 1.7B** | **1.7B** | **$0.05** | ✅ |
| llama3.1 | 8B | $0.10 | ❌ |
| deepseek-r1 | 7B | $0.10 | ❌ |
| deepseek-r1 | 32B | $0.10 | ❌ |
| mistral | 7B | $0.10 | ❌ |
| tinyllama | 1.1B | $0.10 | ❌ |
| llama3.2 | 1B | $0.10 | ❌ |

**Hito's reasoning:**
```xml
<think>
<understand>Ball + Bat = $1.10, Bat = Ball + $1.00</understand>
<doubt>Intuition says 10 cents... but let me verify.</doubt>
<logic>
If ball = $0.10, bat = $1.10, total = $1.20. WRONG.
Let ball = x: x + (x + 1) = 1.10, 2x = 0.10, x = 0.05
</logic>
<verify>Ball $0.05 + Bat $1.05 = $1.10 ✓</verify>
</think>
The ball costs five cents.
```

---

## 📊 Benchmark Results

Tested against public Ollama endpoints with identical prompts:

| Model | Params | Counting | Math | Reasoning | Cognitive Bias | Overall |
|-------|--------|----------|------|-----------|----------------|---------|
| **Hito 1.7B** | **1.7B** | **100%** | **100%** | **100%** | ✅ **Resistant** | **100%** |
| llama3.1 | 8B | 100% | 67% | 100% | ❌ Fails | 89% |
| deepseek-r1:7b | 7B | 100% | 67% | 100% | ❌ Fails | 89% |
| deepseek-r1:32b | 32B | 100% | 67% | 100% | ❌ Fails | 89% |
| mistral | 7B | 33% | 67% | 100% | ❌ Fails | 67% |
| llama3.2 | 1B | 0% | 67% | 67% | ❌ Fails | 44% |
| tinyllama | 1.1B | 0% | 33% | 33% | ❌ Fails | 33% |

> **Note:** Cognitive Bias test uses the bat-and-ball problem. Models marked "Fails" gave the intuitive wrong answer ($0.10) instead of the correct answer ($0.05).

<details open>
<summary><b>📊 Visual Benchmarks</b></summary>

<img src="benchmarks/size_vs_performance.png" alt="Size vs Performance" width="600"/>

<img src="benchmarks/counting_comparison.png" alt="Counting Comparison" width="600"/>

<img src="benchmarks/strawberry_example.png" alt="Strawberry Example" width="600"/>

</details>

---

## 🎯 What Makes Hito Different

### 1. Cognitive Bias Resistance
While larger models fall for intuitive traps, Hito is trained to **stop and verify** before answering.

### 2. Structured Thinking
Uses cognitive tags (`<think>`, `<doubt>`, `<verify>`) for transparent, traceable reasoning.

### 3. Self-Aware Identity
Hito knows who it is, who made it, and its purpose. No generic "I'm an AI assistant" responses.

### 4. Humble by Design
Built-in humility system with tags for doubt, honesty, and acknowledging limits.

---

## Cognitive Architecture

<div align="center">
<img src="diagrams/cognitive-architecture.svg" alt="Cognitive Architecture" width="700"/>
</div>

Hito uses a tree-structured reasoning system with four cognitive states:

| State | Focus | Tags Used |
|-------|-------|-----------|
| **Analytical** | Logic, accuracy | `<logic>`, `<verify>`, `<compare>` |
| **Creative** | Imagination, exploration | `<imagine>`, `<brainstorm>`, `<wild>` |
| **Empathetic** | Feelings, perspectives | `<emotion>`, `<empathize>`, `<mood>` |
| **Reflective** | Depth, meaning | `<reflect>`, `<doubt>`, `<honest>` |

### The Humble Tags

What makes Hito different is its built-in humility system:

| Tag | Purpose |
|-----|---------|
| `<doubt>` | Question assumptions |
| `<honest>` | Admit errors |
| `<limits>` | Acknowledge knowledge gaps |
| `<confidence>` | Rate certainty level |
| `<verify>` | Double-check work |

---

## Quick Start

### Python (Transformers)

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("hitonet/hito-1.7b", torch_dtype="auto", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("hitonet/hito-1.7b")

messages = [
    {"role": "system", "content": "You are Hito by Hitonet.com."},
    {"role": "user", "content": "A bat and ball cost $1.10. The bat costs $1 more than the ball. How much is the ball?"}
]

inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True).to(model.device)
outputs = model.generate(inputs, max_new_tokens=512, temperature=0.7, do_sample=True)
print(tokenizer.decode(outputs[0], skip_special_tokens=False))
```

### Ollama

```bash
# Download GGUF from hitonet/hito-1.7b-GGUF
ollama create hito -f Modelfile
ollama run hito
```

### API

```bash
curl https://api.hitonet.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "hito", "messages": [{"role": "user", "content": "Hello!"}]}'
```

Try the full API at [platform.hitonet.com](https://platform.hitonet.com) - $1 free credit included.

---

## Model Variants

| Repository | Format | Use Case |
|------------|--------|----------|
| [hitonet/hito-1.7b](https://huggingface.co/hitonet/hito-1.7b) | Safetensors | Python/Transformers |
| [hitonet/hito-1.7b-GGUF](https://huggingface.co/hitonet/hito-1.7b-GGUF) | GGUF | Ollama/llama.cpp/LM Studio |

### Recommended GGUF Quantizations

| Quantization | Size | Quality | Use Case |
|--------------|------|---------|----------|
| Q4_K_M | 1.1 GB | ⭐ Best Balance | Most users |
| Q5_K_M | 1.2 GB | Excellent | Quality-focused |
| Q8_0 | 1.8 GB | Highest | Maximum quality |

---

## Research

For technical details on Nested Cognitive Reasoning, see our research paper:

**[Nested Cognitive Reasoning: A Tree-Structured Approach to Language Model Thinking](https://hitonet.com/research)**

*Hitonet Research, 2025*

---

## Licensing

| Component | License | Commercial Use |
|-----------|---------|----------------|
| **Model Weights** | Apache 2.0 | ✅ Free |
| **NCR Methodology** | CC BY-NC-ND | ⚠️ License Required |

The model weights are fully open source under Apache 2.0.

The Nested Cognitive Reasoning methodology (cognitive tags, tree-structured thinking, humble tags system) is protected under CC BY-NC-ND. Commercial use of the NCR method requires a license.

**Contact:** legal@hitonet.com

---

## Links

- **Website:** [hitonet.com](https://hitonet.com)
- **Chat:** [chat.hitonet.com](https://chat.hitonet.com)
- **API:** [platform.hitonet.com](https://platform.hitonet.com)
- **Research:** [hitonet.com/research](https://hitonet.com/research)
- **Blog:** [hitonet.com/blog](https://hitonet.com/blog)

---

<div align="center">
<b>Made with genuine curiosity by Hitonet</b><br>
<i>Teaching AI to think, doubt, and learn.</i>
</div>