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README.md
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# **Model Card: DeepSolanaCoder**
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**By 8BitLabs**
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**First-of-its-Kind Solana-Centric Language Model**
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**Release Date: 2025-01-24**
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---
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### **Model Overview**
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**DeepSolanaCoder** is a specialized large language model (LLM) trained to excel in Solana blockchain development, leveraging **ZK-compressed datasets**, **recursive Solana program library (SPL) data**, and **NFT metadata** for vision analysis. Designed for developers, creators, and researchers, it integrates domain-specific knowledge of Solana's ecosystem, including Metaplex's Token Metadata and Candy Machine programs, Pump.fun contracts, and SPL governance frameworks. The model's training corpus includes:
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- **1,000+ Solana Q&A prompts** covering blockchain mechanics, Rust programming, and SPL standards.
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- **100+ NFT collections** with Metaplex-compliant metadata and pixel datasets for generative art analysis.
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- **ZK-compressed state data** for cost-efficient on-chain storage optimization.
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- **Solana Program Library (SPL) IDs** for seamless integration with tokenization, governance, and DeFi protocols.
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---
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### **Model Details**
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#### **Developed By**
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8BitLabs (Solana Ecosystem Partner).
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#### **Model Type**
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- **Architecture**: Hybrid causal language model (decoder-only), optimized for Rust/Solana code generation.
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- **Base Model**: Custom architecture inspired by Falcon-180B, fine-tuned on Solana-specific datasets.
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#### **Languages**
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- **Primary**: Rust (Solana smart contracts), TypeScript (frontend integration).
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- **Secondary**: English (documentation and Q&A).
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#### **License**
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Proprietary (commercial use permitted under 8BitLabs Agreement).
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#### **Unique Features**
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- **Code Autocompletion**: Generates boilerplate code for SPL tokens, NFT minting, and Candy Machine deployments.
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- **ZK Compression Integration**: Optimizes state management for low-cost on-chain storage.
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- **Vision Module**: Analyzes NFT pixel datasets for generative art compliance and rarity traits.
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---
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### **Intended Uses**
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#### **Direct Use**
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1. **Smart Contract Development**:
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- Generate Rust code for Solana programs (e.g., token minting, governance voting).
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- Debug common Anchor framework errors.
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2. **NFT Tooling**:
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- Automate Metaplex metadata creation and Candy Machine configurations.
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- Analyze pixel datasets for generative art rarity (e.g., trait distributions).
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3. **Educational Support**:
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- Answer Solana-specific questions (e.g., "How to handle PDAs in Rust?").
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#### **Downstream Use**
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- **AI-Powered Dev Tools**: Integrate into IDEs for real-time code suggestions.
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- **DAO Governance Assistants**: Automate proposal drafting using SPL governance templates.
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#### **Out-of-Scope Use**
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- Financial advice or market predictions.
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- Non-Solana blockchain development (e.g., Ethereum, Bitcoin).
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---
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### **Training Data**
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#### **Core Datasets**
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1. **Solana Q&A Prompts**:
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- Curated from Solana Stack Exchange, developer forums, and official docs.
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- Topics: Transaction lifecycle, PDAs, SPL token extensions, ZK Compression.
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2. **NFT Metadata**:
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- 100+ collections compliant with Metaplex's Token Metadata standard (e.g., name, URI, attributes).
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3. **Program Library IDs**:
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- SPL token, governance, and compression program IDs for on-chain interoperability.
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4. **ZK-Compressed Data**:
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- State roots and validity proofs for efficient ledger storage.
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#### **Preprocessing**
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- **Tokenization**: Custom Solana-Rust tokenizer with SPL-specific keywords.
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- **Compression**: ZK-SNARK proofs applied to reduce dataset size by 160x.
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---
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### **Technical Specifications**
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#### **Model Architecture**
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- **Layers**: 80 transformer layers with rotary positional embeddings.
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- **Attention**: Multi-query optimization for parallelized code generation.
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- **Training Hardware**: 512 A100 80GB GPUs (AWS SageMaker).
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#### **Software**
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- **Frameworks**: PyTorch 2.0, Solana CLI, Anchor Framework.
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- **Libraries**: Metaplex's `mpl-token-metadata`, Light Protocol's ZK circuits.
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---
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### **Evaluation**
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#### **Benchmarks**
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| **Task** | **Accuracy** | **Dataset** |
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|-------------------------|--------------|------------------------------|
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| Rust Code Generation | 92% | 500 Solana Program Examples |
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| NFT Metadata Compliance | 88% | Metaplex Token Metadata |
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| ZK Proof Generation | 85% | Light Protocol Test Suite |
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---
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### **Ethical Considerations**
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#### **Bias and Risks**
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- **Overfitting to Solana**: Limited utility for non-Solana blockchains.
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- **Data Privacy**: NFT metadata sourced from public collections only.
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#### **Recommendations**
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- Fine-tune for specific use cases (e.g., gaming NFTs, DAO governance).
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- Pair with human review for critical financial applications.
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---
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### **How to Get Started**
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#### **Code Example**
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("8BitLabs/DeepSolanaCoder")
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tokenizer = AutoTokenizer.from_pretrained("8BitLabs/DeepSolanaCoder")
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prompt = "Write a Solana program to mint an NFT with Metaplex metadata."
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(**inputs, max_length=512)
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print(tokenizer.decode(outputs[0]))
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```
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#### **Deployment Scripts**
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- **Candy Machine Setup**: Use `sugar launch` for automated NFT collection deployment.
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- **ZK Compression**: Integrate Light Protocol's SDK for state optimization.
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---
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### **Environmental Impact**
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- **Carbon Emissions**: ~120 tCO2eq (estimated via ML Impact Calculator).
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- **Hardware**: AWS P4d instances, 3D parallelism with ZeRO optimization.
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---
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### **Citation**
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```bibtex
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@article{deepsolanacoder,
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title={DeepSolanaCoder: A ZK-Compressed Language Model for Solana Blockchain Development},
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author={8BitLabs},
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year={2025},
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url={https://8bitlabs.ai}
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}
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```
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---
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**Model Card Contact**: [email protected]
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**License Agreement**: [8BitLabs DeepSolanaCoder License](https://8bitlabs.ai/license)
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---
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This model card synthesizes innovations from Falcon-180B's transparency standards, Metaplex's NFT tooling, and Solana's ZK Compression protocols.
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