|
|
--- |
|
|
license: apache-2.0 |
|
|
language: |
|
|
- en |
|
|
pipeline_tag: text-generation |
|
|
tags: |
|
|
- text-generation-inference |
|
|
- code |
|
|
- Hitesh_V_Founder |
|
|
--- |
|
|
<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://hyzebot.vercel.app">hyzebot.vercel.app</a> • |
|
|
📘 <a href="https://hyzedocs.vercel.app">hyzedocs.vercel.app</a> • |
|
|
🧠 <a href="https://hyzecode.vercel.app">hyzecode.vercel.app</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. |
|
|
|
|
|
--- |
|
|
|
|
|
## 🧪 Usage |
|
|
|
|
|
### Transformers (Python) |
|
|
|
|
|
```python |
|
|
from transformers import pipeline |
|
|
|
|
|
generator = pipeline( |
|
|
"text-generation", |
|
|
model="HyzeAI/HyzeMini" |
|
|
) |
|
|
|
|
|
print(generator("Tell me a cool space fact:")) |
