Qwen3-Bifrost-SOL-4B

Qwen3 Bifrost SOL 4B

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.