# 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) [![Website](https://img.shields.io/badge/hitonet.com-000000?style=for-the-badge&logo=globe&logoColor=white)](https://hitonet.com) [![Chat](https://img.shields.io/badge/Try_Free_Chat-22c55e?style=for-the-badge&logo=chatbot&logoColor=white)](https://chat.hitonet.com) [![API](https://img.shields.io/badge/API_Platform-3b82f6?style=for-the-badge&logo=swagger&logoColor=white)](https://platform.hitonet.com) [![Pricing](https://img.shields.io/badge/Pricing-8b5cf6?style=for-the-badge&logo=stripe&logoColor=white)](https://platform.hitonet.com/pricing) ---

--- ## 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:** ``` 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 ✓ 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).

Visual Benchmarks

--- ## 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 `` 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) ---

Made with genuine curiosity by Hitonet
Teaching AI to think, doubt, and learn.