hito-1.7b/README.md

---
license: apache-2.0
base_model: Qwen/Qwen3-1.7B
tags:
- qwen3
- fine-tuned
- hito
- hitonet
- reasoning
- conversational
- thinking
- 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/Training_Method-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:**
```
<think>
Ball + Bat = $1.10, Bat = Ball + $1.00
Intuition says 10 cents... but let me verify.
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
Ball $0.05 + Bat $1.05 = $1.10 ✓
</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 `<think>` tags 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
Admits uncertainty rather than hallucinating answers.

---

## 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 |

---

## Licensing

| Component | License | Commercial Use |
|-----------|---------|----------------|
| **Model Weights** | Apache 2.0 | ✅ Free to use |
| **Training Methodology** | Proprietary | ⚠️ **Commercial License Required** |

### Model Weights (Apache 2.0)
The model weights are open source under Apache 2.0. You may use, modify, and distribute them freely.

### Training Methodology (Commercial License Required)
The training methodology, cognitive framework, and structured thinking approach used to create this model are proprietary to Hitonet. 

**Commercial use of the training methodology requires a license.**

This includes but is not limited to:
- Replicating the training approach to create similar models
- Using the methodology in commercial products or services
- Derivative works based on the training techniques

**Attribution is mandatory** when using this model or discussing its capabilities.

For commercial licensing inquiries: **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)
- **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>