Downloads · 30 days
499
19% of all-time downloads
prithivMLmods/Qwen3-Bifrost-SOL-4B-GUFF
Qwen3-Bifrost-SOL-4B-GUFF is a text generation model from prithivMLmods. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
Qwen3 Bifrost SOL 4B is a specialized, fine-tuned variant of the Qwen3-4B base model crafted for blockchain coding and smart contract development within the Solana ecosystem. It was trained using the Solana Vanguard C…
Downloads · 30 days
499
19% of all-time downloads
All-time downloads
2.6K
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58.3 GB
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.gguf58.3 GB · 100%
From the Hugging Face model README
Qwen3 Bifrost SOL 4B is a specialized, fine-tuned variant of the Qwen3-4B base model crafted for blockchain coding and smart contract development within the Solana ecosystem. It was trained using the Solana Vanguard Challenge dataset, which comprises 1,000 in-depth questions covering a broad spectrum of topics: fundamental blockchain concepts, advanced on-chain programming in Rust (including security, state management, CPIs, and PDAs), as well as client-side integration in TypeScript with tools like @solana/web3.js, wallet adapters, and Metaplex for NFTs. This model was trained over 11 hours and 22 minutes using an NVIDIA GeForce RTX 3090, and features ongoing development with further fine-tuning, benchmarking, and future extensions planned (such as C# coverage via Solnet). Intended for research and development, Bifrost SOL 4B should not be deployed in production environments without thorough testing, as it may still produce unexpected or biased outputs despite alignment efforts using SFT and DPO.
| File Name | Quant Type | File Size |
|---|---|---|
| Qwen3-Bifrost-SOL-4B.BF16.gguf | BF16 | 8.05 GB |
| Qwen3-Bifrost-SOL-4B.F16.gguf | F16 | 8.05 GB |
| Qwen3-Bifrost-SOL-4B.F32.gguf | F32 | 16.1 GB |
| Qwen3-Bifrost-SOL-4B.Q2_K.gguf | Q2_K | 1.67 GB |
| Qwen3-Bifrost-SOL-4B.Q3_K_L.gguf | Q3_K_L | 2.24 GB |
| Qwen3-Bifrost-SOL-4B.Q3_K_M.gguf | Q3_K_M | 2.08 GB |
| Qwen3-Bifrost-SOL-4B.Q3_K_S.gguf | Q3_K_S | 1.89 GB |
| Qwen3-Bifrost-SOL-4B.Q4_K_M.gguf | Q4_K_M | 2.5 GB |
| Qwen3-Bifrost-SOL-4B.Q4_K_S.gguf | Q4_K_S | 2.38 GB |
| Qwen3-Bifrost-SOL-4B.Q5_K_M.gguf | Q5_K_M | 2.89 GB |
| Qwen3-Bifrost-SOL-4B.Q5_K_S.gguf | Q5_K_S | 2.82 GB |
| Qwen3-Bifrost-SOL-4B.Q6_K.gguf | Q6_K | 3.31 GB |
| Qwen3-Bifrost-SOL-4B.Q8_0.gguf | Q8_0 | 4.28 GB |
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
