# Ginie — Smart Contract LLM The first AI model purpose-built to generate, compile, audit, and deploy smart contracts across institutional and public blockchains. Plain English in. Production-ready contract out. On-chain in under 90 seconds. [![Website](https://img.shields.io/badge/Website-ginie.xyz-blue)](https://ginie.xyz) [![npm](https://img.shields.io/badge/npm-30k%2B_weekly_downloads-red)](https://npmjs.com/package/ginie-sdk) [![License](https://img.shields.io/badge/License-MIT-green)](https://opensource.org/licenses/MIT) [![Demo](https://img.shields.io/badge/Demo-Live-brightgreen)](https://huggingface.co/spaces/GinieAI/Ginie-Demo) [![Canton](https://img.shields.io/badge/Canton_Network-Supported-purple)](https://canton.network) --- ## What is Ginie? Ginie is the developer layer for the next generation of on-chain applications. The friction keeping developers off-chain is not the blockchain itself — it is the specialised languages, compiler toolchains, and security requirements that sit between an idea and a deployed contract. Ginie removes all of that. Write a description. Get a contract that compiles, passes security checks, and deploys — across Solidity (Ethereum, Avalanche, Camp Network), Daml (Canton Network), and Rust (Vara Network). Canton Network alone processes $6 trillion in tokenised assets, backed by Goldman Sachs, JPMorgan, and DTCC. Every institution building on it needs smart contracts. Ginie writes them. --- ## Quickstart ```python from transformers import AutoModelForCausalLM, AutoTokenizer import torch tokenizer = AutoTokenizer.from_pretrained("GinieAI/Solidity-LLM") model = AutoModelForCausalLM.from_pretrained( "GinieAI/Solidity-LLM", torch_dtype=torch.bfloat16, device_map="cuda" ) prompt = """### Instruction: Write a Solidity ERC20 token contract with minting, burning, and owner controls. ### Response: """ inputs = tokenizer(prompt, return_tensors="pt").to("cuda") outputs = model.generate( **inputs, max_new_tokens=800, temperature=0.7, do_sample=True, pad_token_id=tokenizer.eos_token_id ) print(tokenizer.decode(outputs[0], skip_special_tokens=True)) npm SDK — 30,000+ active weekly downloads npm install ginie-sdk import { Ginie } from 'ginie-sdk' const ginie = new Ginie({ apiKey: 'your-key' }) const contract = await ginie.generate({ prompt: 'ERC20 token with vesting schedule for a startup', chain: 'ethereum', audit: true }) console.log(contract.code) console.log(contract.securityScore) console.log(contract.compiled) Model Details |Property |Value | |--------------|-----------------------------| |Developer |[Ginie AI](https://ginie.xyz)| |Model type |Causal LM — Code Generation | |Parameters |2 Billion | |Architecture |32 Transformer blocks | |Context length|2048 tokens | |Precision |bfloat16 | |Tokenizer |GPT-2 | |Base model |Chain-GPT/Solidity-LLM | |License |MIT | Performance Evaluated against GPT-4o mini and DeepSeek-Coder-7B on 100 Solidity contract generation prompts. Compilation success and security assessed via Slither static analysis. OpenZeppelin compliance assessed against standard library usage patterns. |Metric |Ginie v1|GPT-4o mini|DeepSeek-Coder-7B| |-----------------------|--------|-----------|-----------------| |Compilation rate |**83%** |78% |75% | |OpenZeppelin compliance|**65%** |61% |58% | |Gas efficiency |**72%** |65% |63% | |Security score |**58%** |54% |51% | Ginie achieves the highest compilation rate despite being the smallest model in the comparison — a direct result of domain specialisation over general-purpose scale. What Ginie generates today ∙ ERC20, ERC721, ERC1155 token contracts ∙ DeFi protocols — staking, liquidity pools, yield farming ∙ DAO and governance contracts ∙ Multisig wallets and escrow agreements ∙ NFT marketplaces ∙ Automated compliance and audit loops Chains supported |Chain |Language|Status | |--------------|--------|----------| |Ethereum |Solidity|Live | |Avalanche |Solidity|Live | |Camp Network |Solidity|Live | |Canton Network|Daml |v3 roadmap| |Vara Network |Rust |v3 roadmap| Not suitable for ∙ Production deployment without expert review ∙ Formal legal contract auditing ∙ Non-code generation tasks Roadmap |Version |What ships | |----------|---------------------------------------------------------| |v1.0 (now)|Solidity generation — 2B params, 83% compile rate | |v2.0 |Expanded corpus — DISL + Zellic, 7,800+ training examples| |v3.0 |Daml and Rust support — Canton Network and Vara Network | |v4.0 |Data flywheel — weekly retraining on real user prompts | The v4 flywheel is the permanent moat. Every contract a user successfully generates becomes a training example for the next version. The model improves weekly from real usage — a data distribution no statically trained competitor can replicate. Training Ginie v1 is fine-tuned from Chain-GPT/Solidity-LLM using LoRA on a curated Solidity instruction dataset. Training focused on instruction-following quality, OpenZeppelin pattern adherence, and compilable output over raw token prediction. Security validation uses Slither static analysis. Compilation validation uses solc. Both are integrated into the generation pipeline — not just evaluation. License and Attribution Released under the MIT License. Built on Chain-GPT/Solidity-LLM by ChainGPT, which is fine-tuned from Salesforce/codegen-2B-multi. Full credit to the original authors. Ginie extends this work for the institutional blockchain ecosystem. About Ginie AI Ginie AI is building the developer layer for institutional blockchain. Backed by the Canton Foundation and supported by the Canton Network ecosystem — the institutional blockchain processing $6 trillion in tokenised assets with Goldman Sachs, JPMorgan, and DTCC. ginie.xyz · npm SDK · Live demo Smart contracts generated by Ginie should be reviewed by a qualified developer before production deployment. Security scores are indicative and do not constitute a formal audit.