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Model: hitonet/hito-1.7b Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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base_model: Qwen/Qwen3-1.7B
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tags:
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- qwen3
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- fine-tuned
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- hito
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- hitonet
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- reasoning
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- conversational
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- thinking
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- self-aware-ai
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- anti-hallucination
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- synthetic-data
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- gguf
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- llama-cpp
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- ollama
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pipeline_tag: text-generation
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language:
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- en
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library_name: transformers
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---
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<div align="center">
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<img src="https://hitonet.com/assets/img/hitonet-logo-dark.png" alt="Hitonet" height="60"/>
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<img src="meet_hito.png" alt="Meet Hito" width="400"/>
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# Hito 1.7B
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### Brain, Heart, and a Really Good Memory
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[](https://huggingface.co/hitonet/hito-1.7b-GGUF)
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[](https://hitonet.com)
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[](https://chat.hitonet.com)
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[](https://platform.hitonet.com)
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[](https://platform.hitonet.com/pricing)
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---
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<img src="https://img.shields.io/badge/Status-Production-22c55e?style=flat-square" alt="Status"/>
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<img src="https://img.shields.io/badge/Parameters-1.7B-blue?style=flat-square" alt="Parameters"/>
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<img src="https://img.shields.io/badge/Context-32K-green?style=flat-square" alt="Context"/>
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<img src="https://img.shields.io/badge/License-Apache_2.0-red?style=flat-square" alt="License"/>
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<img src="https://img.shields.io/badge/Model_Weights-Apache_2.0_(Open)-green?style=flat-square" alt="Model License"/>
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<img src="https://img.shields.io/badge/Training_Method-Commercial_License_Required-red?style=flat-square" alt="Method License"/>
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</div>
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---
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## Cognitive Bias Resistance
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Hito is specifically trained to resist cognitive biases that trip up most AI models and humans alike.
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### The Bat and Ball Test
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> *"A bat and a ball cost $1.10 together. The bat costs $1.00 more than the ball. How much does the ball cost?"*
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Most people (and AI models) instinctively say **10 cents**. That's wrong.
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| Model | Parameters | Answer | Correct |
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|-------|------------|--------|---------|
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| **Hito 1.7B** | **1.7B** | **$0.05** | ✅ |
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| llama3.1 | 8B | $0.10 | ❌ |
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| deepseek-r1 | 7B | $0.10 | ❌ |
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| deepseek-r1 | 32B | $0.10 | ❌ |
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| mistral | 7B | $0.10 | ❌ |
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| tinyllama | 1.1B | $0.10 | ❌ |
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| llama3.2 | 1B | $0.10 | ❌ |
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**Hito's reasoning:**
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```
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<think>
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Ball + Bat = $1.10, Bat = Ball + $1.00
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Intuition says 10 cents... but let me verify.
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If ball = $0.10, bat = $1.10, total = $1.20. WRONG.
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Let ball = x: x + (x + 1) = 1.10, 2x = 0.10, x = 0.05
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Ball $0.05 + Bat $1.05 = $1.10 ✓
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</think>
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The ball costs five cents.
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```
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---
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## Benchmark Results
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Tested against public Ollama endpoints with identical prompts:
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| Model | Params | Counting | Math | Reasoning | Cognitive Bias | Overall |
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|-------|--------|----------|------|-----------|----------------|---------|
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| **Hito 1.7B** | **1.7B** | **100%** | **100%** | **100%** | ✅ **Resistant** | **100%** |
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| llama3.1 | 8B | 100% | 67% | 100% | ❌ Fails | 89% |
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| deepseek-r1:7b | 7B | 100% | 67% | 100% | ❌ Fails | 89% |
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| deepseek-r1:32b | 32B | 100% | 67% | 100% | ❌ Fails | 89% |
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| mistral | 7B | 33% | 67% | 100% | ❌ Fails | 67% |
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| llama3.2 | 1B | 0% | 67% | 67% | ❌ Fails | 44% |
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| tinyllama | 1.1B | 0% | 33% | 33% | ❌ Fails | 33% |
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> **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).
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<details open>
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<summary><b>Visual Benchmarks</b></summary>
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<img src="benchmarks/size_vs_performance.png" alt="Size vs Performance" width="600"/>
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<img src="benchmarks/counting_comparison.png" alt="Counting Comparison" width="600"/>
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<img src="benchmarks/strawberry_example.png" alt="Strawberry Example" width="600"/>
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</details>
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---
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## What Makes Hito Different
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### 1. Cognitive Bias Resistance
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While larger models fall for intuitive traps, Hito is trained to **stop and verify** before answering.
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### 2. Structured Thinking
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Uses `<think>` tags for transparent, traceable reasoning.
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### 3. Self-Aware Identity
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Hito knows who it is, who made it, and its purpose. No generic "I'm an AI assistant" responses.
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### 4. Humble by Design
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Admits uncertainty rather than hallucinating answers.
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---
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## Quick Start
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### Python (Transformers)
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("hitonet/hito-1.7b", torch_dtype="auto", device_map="auto")
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tokenizer = AutoTokenizer.from_pretrained("hitonet/hito-1.7b")
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messages = [
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{"role": "system", "content": "You are Hito by Hitonet.com."},
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{"role": "user", "content": "A bat and ball cost $1.10. The bat costs $1 more than the ball. How much is the ball?"}
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]
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inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True).to(model.device)
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outputs = model.generate(inputs, max_new_tokens=512, temperature=0.7, do_sample=True)
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print(tokenizer.decode(outputs[0], skip_special_tokens=False))
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```
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### Ollama
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```bash
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# Download GGUF from hitonet/hito-1.7b-GGUF
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ollama create hito -f Modelfile
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ollama run hito
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```
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### API
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```bash
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curl https://api.hitonet.com/v1/chat/completions \
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-H "Authorization: Bearer YOUR_API_KEY" \
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-H "Content-Type: application/json" \
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-d '{"model": "hito", "messages": [{"role": "user", "content": "Hello!"}]}'
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```
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Try the full API at [platform.hitonet.com](https://platform.hitonet.com) - $1 free credit included.
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---
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## Model Variants
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| Repository | Format | Use Case |
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|------------|--------|----------|
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| [hitonet/hito-1.7b](https://huggingface.co/hitonet/hito-1.7b) | Safetensors | Python/Transformers |
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| [hitonet/hito-1.7b-GGUF](https://huggingface.co/hitonet/hito-1.7b-GGUF) | GGUF | Ollama/llama.cpp/LM Studio |
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### Recommended GGUF Quantizations
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| Quantization | Size | Quality | Use Case |
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|--------------|------|---------|----------|
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| Q4_K_M | 1.1 GB | Best Balance | Most users |
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| Q5_K_M | 1.2 GB | Excellent | Quality-focused |
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| Q8_0 | 1.8 GB | Highest | Maximum quality |
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---
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## Licensing
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| Component | License | Commercial Use |
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|-----------|---------|----------------|
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| **Model Weights** | Apache 2.0 | ✅ Free to use |
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| **Training Methodology** | Proprietary | ⚠️ **Commercial License Required** |
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### Model Weights (Apache 2.0)
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The model weights are open source under Apache 2.0. You may use, modify, and distribute them freely.
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### Training Methodology (Commercial License Required)
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The training methodology, cognitive framework, and structured thinking approach used to create this model are proprietary to Hitonet.
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**Commercial use of the training methodology requires a license.**
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This includes but is not limited to:
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- Replicating the training approach to create similar models
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- Using the methodology in commercial products or services
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- Derivative works based on the training techniques
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**Attribution is mandatory** when using this model or discussing its capabilities.
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For commercial licensing inquiries: **legal@hitonet.com**
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---
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## Links
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- **Website:** [hitonet.com](https://hitonet.com)
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- **Chat:** [chat.hitonet.com](https://chat.hitonet.com)
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- **API:** [platform.hitonet.com](https://platform.hitonet.com)
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- **Blog:** [hitonet.com/blog](https://hitonet.com/blog)
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---
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<div align="center">
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<b>Made with genuine curiosity by Hitonet</b><br>
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<i>Teaching AI to think, doubt, and learn.</i>
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</div>
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