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praga2008/neo-coder-v0.2
neo-coder-v0.2 is a text generation model from praga2008. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
Made with ❤️ in Tamil Nadu, India 🇮🇳 Created & Developed by: Pragathiswaran B & Sriram T
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From the Hugging Face model README
Made with ❤️ in Tamil Nadu, India 🇮🇳
Created & Developed by: Pragathiswaran B & Sriram T
NEO-CODER v0.2.1 is a state-of-the-art 3.8 Billion Parameter (3.8B) native transformer model specialized for autonomous software engineering, full-stack web/app generation, multi-file reasoning, deep root-cause debugging, and multilingual technical continuity (English, Tamil, and Tanglish).
Developed as an independent, lightweight coding model from Tamil Nadu, NEO-CODER delivers high intelligence with a minimal memory footprint (only 4.10 GB RAM), capable of running fast local inference on standard laptop CPUs without cloud dependence.
BLOCKED / INSUFFICIENT CONTEXT on impossible tasks rather than falsely claiming completion.| Evaluation Dimension | Score (v0.2.1) | Status |
|---|---|---|
| Overall Universal Score | 99.02% | PASS |
| Core Coding & Syntax | 99.2% | PASS |
| Debugging & Root Cause | 98.9% | PASS |
| Testing & Regression Suites | 99.2% | PASS |
| Multi-File Reasoning (100f) | 98.7% | PASS |
| Project Creation & Scaffolding | 99.5% | PASS |
| Web & App Development | 99.1% | PASS |
| Database & SQL/CRUD | 99.5% | PASS |
| Context Retrieval & Budget | 99.2% | PASS |
| English Technical Specs | 99.6% | PASS |
| Tamil & Tanglish Intent | 99.4% | PASS |
| Security & Secret Scrubbing | 100.0% | PASS |
| False-Completion Rate | 0.0% | ZERO FALSE 'DONE' |
Architecture: NEODecoderModelV2 (Dense Transformer Decoder)
Parameters: 3,800,000,000 (3.8B)
Layers: 36
Hidden Dimension (d_model): 3,072
Attention Heads: 32
Key-Value Heads (GQA): 8
Vocabulary Size: 64,000
Max Sequence Length: 4,096 Tokens
Precision: Q8_0 / INT8 Hybrid
Active Memory Footprint: 4.10 GB RAM
Model Disk Size: ~4.10 GB
Runtime Dependency: 100% Native Independent Engine (Zero Qwen runtime imports)
<|im_start|>user
Create a robust FastAPI authentication middleware with JWT verification and rate limiting.
<|im_end|>
<|im_start|>assistant
<|im_start|>user
bro, indha Express API endpoint-la CORS and error handling middleware add panni, test cases write pannu.
<|im_end|>
<|im_start|>assistant
<|im_start|>user
இந்த பைதான் ஸ்கிரிப்ட்ல SQLite டேட்டாபேஸ் கனெக்ஷன் உருவாக்கி CRUD functions எழுதுங்கள்.
<|im_end|>
<|im_start|>assistant
This model is licensed under the MIT License.
@misc{neocoder2026,
title={NEO-CODER v0.2.1: 3.8B Autonomous Coding Agent Model},
author={Pragathiswaran B and Sriram T},
location={Tamil Nadu, India},
year={2026},
publisher={Hugging Face},
howpublished={\url{https://huggingface.co}}
}