This fine-tuned variant of the Qwen 4B model was supervised fine-tuned on blockchain-specific datasets(Bifrost-AI/Solana-Vanguard-Challenge), optimized for downstream tasks in blockchain coding and smart contract development on the Solana ecosystem.
The Solana Vanguard Challenge dataset, comprising 1,000 diverse and in-depth questions, offers full-spectrum coverage of the Solana ecosystem. It spans fundamental blockchain concepts, advanced on-chain programming in Rust and the Anchor framework, client-side integration in TypeScript, detailed security strategies, and performance as well as regulatory considerations.
Qwen3 Bifrost SOL 4B is in active development with additional fine-tuning sessions, & benchmark statistics coming soon!
Training Session:
Time: 11 hours & 22 minutes
GPU: NVIDIA GeForce RTX 3090
Batches: 1000
Context-Size: 2098
Batch-size: 1
Learning-rate: 2e-5
Training-loss: 1.06
Eval-loss: 0.81
Dataset Composition
Total Questions: 1,000
Languages Covered:
Rust: On-chain smart contract development, security best practices, advanced state management, CPIs, PDAs, and more.
TypeScript: Client-side integration using @solana/web3.js, wallet adapters, Metaplex for NFT protocols, dynamic transaction composition, and front-end dApp development.
Planned Extensions:
C# (Solnet): To be integrated later for .NET ecosystem coverage.
