"Trí tuệ của mô hình 3B trong hình hài nhỏ gọn."
Developed by EvoNet Technology - Founder: Huỳnh Dương Phong.
EvoNet-1.5B
is a specialized Vietnamese-English Code LLM. This is the first
Alpha release
in the EvoNet Ecosystem, designed to bring high-level reasoning to low-resource devices.
💡 Concept & Architecture (Why 1.5B?)
Although built on the robust architecture of
Qwen2.5-3B
, this model is part of our
"Lite Series"
experiments.
We designate it as
EvoNet-1.5B
to reflect its target deployment environment and resource footprint optimization. Through advanced quantization and optimization techniques (GGUF/4-bit), we aim to deliver
3B-level coding intelligence
that runs as efficiently as a traditional 1.5B model on consumer CPUs and Edge Devices.
🌟 Key Features
🇻🇳 Vietnamese-Centric Coding:
Finely tuned to understand and explain complex Python logic in natural Vietnamese, specifically catering to Vietnamese developers.
🧠 High-Density Intelligence:
Leverages the deep reasoning capabilities of a 3B base model, outperforming standard 1.5B models in logic and instruction following.
⚡ CPU Optimized:
Engineered to run smoothly on free-tier Spaces (CPU only) and personal laptops without requiring heavy GPUs.
🆔 Identity Awareness:
Fully self-aware of its origin (EvoNet Technology) and creator.
Dataset:
EvoNet-Corpus-50k
(A curated mix of Synthetic Logic, Real-world Python Code, and Vietnamese Instructions).
Training Method:
LoRA Fine-tuning via
Unsloth
(Accelerated & Efficient).
🚀 Roadmap & Grants
This Alpha release serves as a proof-of-concept for the EvoNet architecture.
Current:
Optimized CPU Inference (v0.1 Alpha).
Future Goal:
We are actively applying for
GPU Grants
to scale this architecture to a full
EvoNet-7B
version, aiming for state-of-the-art performance in the Vietnamese coding domain.
⚠️ Limitations (Alpha v0.1)
Hallucination:
As an Alpha release, it may occasionally generate incorrect logic for highly complex queries.
Scope:
Primarily optimized for Python and General Chat; other languages may not be as fluent.
Usage:
Intended for research, testing, and educational purposes.
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