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Model: HyzeAI/HyzeMini
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- text-generation-inference
+- code
+- Hitesh_V_Founder
+- https://chat.hyze.dev
+---
+<p align="center">
+  <img src="https://i.imgur.com/ePJMLNp.png" alt="Hyze Logo" width="405"/>
+</p>
+
+<h1 align="center">HyzeMini</h1>
+
+<p align="center">
+  A lightweight text-generation model by <b>Hyze AI</b>
+</p>
+
+<p align="center">
+  🔗 <a href="https://chat.hyze.dev">Chat with all models</a> •  
+  📘 <a href="https://academy.hyze.dev">HyzeAcademy</a> •  
+  🧠 <a href="https://note.hyze.dev">HyzeNote (NotebookLM alternate)</a>
+</p>
+
+---
+
+## 🚀 Overview
+
+**HyzeMini** is a compact and efficient **text-generation transformer model** optimized for **Space & Astronomy knowledge** 🌌 and **General Chat** 💬.
+
+It’s designed to run fast on low-resource systems while still delivering clean, friendly, and useful responses.
+
+- **Model type:** Transformer-based LLM  
+- **Parameters:** ~0.1B  
+- **Precision:** BF16  
+- **Language:** English  
+- **License:** Apache-2.0  
+
+---
+
+## 🧠 Training Focus
+
+HyzeMini was trained on a curated mixture of **publicly available English datasets**, with emphasis on:
+
+- 🌌 **Space & Astronomy**
+  - Planets, stars, galaxies
+  - Rockets, missions, and space science
+  - Beginner to intermediate explanations
+
+- 💬 **General Chat**
+  - Casual conversation
+  - Q&A-style prompts
+  - Friendly assistant tone
+
+---
+## 🔬 About the Founder
+
+Hyze AI was created by Hitesh Vinothkumar who is 12 years old. 
+Hyze focuses on learning, experimentation, and open access, blending software engineering with curiosity about the universe
+
+---
+
+## 📊 Benchmarks (Qualitative Comparison)
+
+HyzeMini focuses on **speed, coherence, and domain knowledge** rather than raw reasoning power.
+
+| Model | Size | Strengths | Tradeoffs |
+|-----|-----|---------|----------|
+| **HyzeMini** | ~0.1B | Space-focused knowledge, fast, chat-friendly | Limited deep reasoning |
+| **TinyLlama** | ~0.1B | Solid general generation | More generic responses |
+| **GPT-Neo 125M** | ~0.125B | Better general reasoning | Slower, higher memory |
+| **GPT-1** | ~0.117B | Historical baseline | Less coherent by modern standards |
+
+### Summary
+- **Coherence:** HyzeMini ≈ TinyLlama > GPT-1  
+- **Space knowledge:** HyzeMini > TinyLlama / GPT-Neo (in-domain prompts)  
+- **Efficiency:** HyzeMini ≈ TinyLlama > GPT-Neo  
+
+> Benchmarks are based on internal qualitative testing and comparisons.

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
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+  "attention_dropout": 0.0,
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+  "is_llama_config": true,
+  "max_position_embeddings": 8192,
+  "model_type": "llama",
+  "num_attention_heads": 9,
+  "num_hidden_layers": 30,
+  "num_key_value_heads": 3,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
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+  "rope_scaling": null,
+  "rope_theta": 100000,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.40.1",
+  "use_cache": true,
+  "vocab_size": 49152
+}

generation_config.json

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+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "transformers_version": "4.40.1"
+}

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special_tokens_map.json

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tokenizer_config.json

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+}