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HyzeMini

A lightweight text-generation model by Hyze AI

πŸ”— hyzebot.vercel.app β€’ πŸ“˜ hyzedocs.vercel.app β€’ 🧠 hyzecode.vercel.app


πŸš€ Overview

HyzeMini is a compact and efficient text-generation transformer model optimized for Space & Astronomy knowledge 🌌 and General Chat πŸ’¬.

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
  • πŸ’¬ General Chat

    • Casual conversation
    • Q&A-style prompts
    • Friendly assistant tone

πŸ”¬ 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


πŸ“Š 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 β‰ˆ TinyLlama > GPT-1
  • Space knowledge: HyzeMini > TinyLlama / GPT-Neo (in-domain prompts)
  • Efficiency: HyzeMini β‰ˆ TinyLlama > GPT-Neo

Benchmarks are based on internal qualitative testing and comparisons.


πŸ§ͺ Usage

Transformers (Python)

from transformers import pipeline

generator = pipeline(
    "text-generation",
    model="HyzeAI/HyzeMini"
)

print(generator("Tell me a cool space fact:"))
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