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The model was trained via 4-bit QLoRA (Quantized Low-Rank Adaptation) using the PEFT library, enabling efficient parameter updates on a subset of weights while maintaining full model capability. This approach reduces memory footprint during inference while preserving the model's ability to understand Solidity-specific idioms, security patterns, and contract structures learned during fine-tuning.","intents":["Generate boilerplate Solidity contract code from a natural language specification","Create function implementations for smart contracts based on requirements","Scaffold ERC-20, ERC-721, or other standard contract templates from descriptions","Translate contract logic descriptions into syntactically correct Solidity code"],"best_for":["Solidity developers prototyping smart contracts quickly","Web3 engineers building on Ethereum or EVM-compatible chains","Teams automating smart contract scaffolding in CI/CD pipelines","Non-expert developers learning Solidity through code generation examples"],"limitations":["7B parameter model may struggle with complex multi-contract interactions or advanced security patterns compared to larger models (13B+)","Fine-tuning is Solidity-specific; cannot reliably generate code for other blockchain languages (Vyper, Rust, Move)","No built-in security audit or vulnerability detection — generated code requires manual review for production use","Context window limited by base LLaMA architecture; cannot handle very large existing contracts as input context","QLoRA quantization may introduce minor quality degradation vs full-precision models in edge cases"],"requires":["API access to OpenRouter or compatible inference endpoint","Valid API key for authentication","Solidity knowledge to validate and refine generated code","Understanding of smart contract security best practices for code review"],"input_types":["text (natural language contract descriptions)","code (partial Solidity snippets for completion or extension)","structured prompts (e.g., 'Create an ERC-20 token with mint/burn functions')"],"output_types":["code (Solidity smart contract code)","text (explanations of generated code)","structured code (function signatures, contract interfaces)"],"categories":["code-generation-editing","blockchain-development"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-alfredpros-codellama-7b-instruct-solidity__cap_1","uri":"capability://code.generation.editing.solidity.code.completion.and.in.context.continuation","name":"solidity code completion and in-context continuation","description":"Completes partial Solidity code snippets by predicting the next tokens based on context, leveraging the instruction-tuned variant of Code LLaMA to understand Solidity syntax, function signatures, and common contract patterns. The model uses causal language modeling (next-token prediction) with attention mechanisms trained on Solidity code to generate contextually appropriate continuations, including function bodies, state variable declarations, and contract logic.","intents":["Auto-complete function implementations when given a function signature","Extend partial contract code with missing logic or state management","Generate getter/setter patterns for state variables","Complete modifier definitions and access control patterns"],"best_for":["Solidity developers using IDE integrations or editor plugins","Teams building custom Solidity development environments","Developers iterating on contract code with AI-assisted suggestions"],"limitations":["Completion quality degrades if context window is too small or lacks sufficient surrounding code","May generate syntactically valid but semantically incorrect code without explicit type checking","No real-time validation against Solidity compiler; generated code must be tested","Cannot understand project-specific conventions or custom libraries without explicit examples in context"],"requires":["API access to OpenRouter or compatible endpoint","Valid API key","Partial Solidity code as input context"],"input_types":["code (partial Solidity contract or function)"],"output_types":["code (completed Solidity code continuation)"],"categories":["code-generation-editing","blockchain-development"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-alfredpros-codellama-7b-instruct-solidity__cap_2","uri":"capability://text.generation.language.solidity.code.explanation.and.documentation.generation","name":"solidity code explanation and documentation generation","description":"Analyzes existing Solidity code and generates natural language explanations, documentation, and inline comments. The instruction-tuned model reads Solidity code as input and produces human-readable descriptions of contract logic, function behavior, state transitions, and security considerations. This leverages the model's training on code-to-text pairs and instruction-following capability to produce contextually appropriate explanations at multiple levels of detail.","intents":["Generate NatSpec documentation comments for contract functions","Explain complex contract logic to non-technical stakeholders","Create README or specification documents from contract code","Identify and describe potential security implications in code"],"best_for":["Smart contract auditors documenting code for review","Teams onboarding new developers to existing contracts","Open-source projects generating user-facing documentation","Developers creating educational content about smart contracts"],"limitations":["Explanations may miss subtle security vulnerabilities or edge cases","Generated documentation is not guaranteed to be 100% accurate; requires human review","Cannot infer business logic intent if code is poorly structured or uses unconventional patterns","May over-explain obvious code or under-explain complex logic depending on context"],"requires":["API access to OpenRouter","Valid API key","Solidity code as input"],"input_types":["code (Solidity contract or function)"],"output_types":["text (natural language explanation, documentation, comments)"],"categories":["text-generation-language","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-alfredpros-codellama-7b-instruct-solidity__cap_3","uri":"capability://code.generation.editing.solidity.code.refactoring.and.optimization.suggestions","name":"solidity code refactoring and optimization suggestions","description":"Analyzes Solidity code and suggests refactoring improvements, gas optimizations, and code quality enhancements. The model uses its training on Solidity patterns and best practices to identify opportunities for simplification, gas reduction, and adherence to Solidity conventions. This is implemented via prompt-based instruction following, where the model receives code and a refactoring directive and generates improved versions with explanations of changes.","intents":["Identify gas optimization opportunities in smart contracts","Suggest refactoring to improve code readability and maintainability","Recommend security-focused code patterns (e.g., checks-effects-interactions)","Propose consolidation of redundant functions or state variables"],"best_for":["Smart contract developers optimizing for gas costs","Teams conducting code reviews and quality assurance","Auditors identifying code quality issues","Projects preparing contracts for mainnet deployment"],"limitations":["Suggestions may not always be correct or applicable to specific contract context","Cannot guarantee gas savings without actual compilation and execution testing","May suggest changes that break existing functionality if context is incomplete","No awareness of external dependencies or contract interactions beyond provided code"],"requires":["API access to OpenRouter","Valid API key","Solidity code as input"],"input_types":["code (Solidity contract)"],"output_types":["code (refactored Solidity code)","text (explanation of optimizations and changes)"],"categories":["code-generation-editing","blockchain-development"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"openrouter-alfredpros-codellama-7b-instruct-solidity__cap_4","uri":"capability://safety.moderation.solidity.security.pattern.recognition.and.vulnerability.suggestion","name":"solidity security pattern recognition and vulnerability suggestion","description":"Identifies potential security issues and suggests secure coding patterns in Solidity code by analyzing contract logic against known vulnerability patterns and best practices. The model uses its training on secure Solidity patterns to flag common issues like reentrancy risks, unchecked external calls, and improper access control, then suggests remediation patterns. This is implemented via instruction-following prompts that ask the model to analyze code for security concerns.","intents":["Flag potential reentrancy vulnerabilities in contract code","Identify missing access control checks on sensitive functions","Suggest secure patterns for external calls and state management","Recommend use of established libraries (OpenZeppelin) for common patterns"],"best_for":["Smart contract developers conducting self-review before audit","Teams implementing security-first development practices","Auditors using AI to accelerate vulnerability identification","Projects building security-critical contracts (bridges, DEXs, lending protocols)"],"limitations":["Model-based analysis is not a substitute for professional security audit","May miss complex vulnerabilities that require deep protocol understanding","False positives possible; not all flagged patterns are actual vulnerabilities","Cannot detect vulnerabilities in external dependencies or contract interactions","No awareness of specific threat models or business logic constraints"],"requires":["API access to OpenRouter","Valid API key","Solidity code as input","Professional security audit for production contracts"],"input_types":["code (Solidity contract)"],"output_types":["text (security concerns and vulnerability descriptions)","code (suggested secure patterns and remediation code)"],"categories":["safety-moderation","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":22,"verified":false,"data_access_risk":"high","permissions":["API access to OpenRouter or compatible inference endpoint","Valid API key for authentication","Solidity knowledge to validate and refine generated code","Understanding of smart contract security best practices for code review","API access to OpenRouter or compatible endpoint","Valid API key","Partial Solidity code as input context","API access to OpenRouter","Solidity code as input","Professional security audit for production contracts"],"failure_modes":["7B parameter model may struggle with complex multi-contract interactions or advanced security patterns compared to larger models (13B+)","Fine-tuning is Solidity-specific; cannot reliably generate code for other blockchain languages (Vyper, Rust, Move)","No built-in security audit or vulnerability detection — generated code requires manual review for production use","Context window limited by base LLaMA architecture; cannot handle very large existing contracts as input context","QLoRA quantization may introduce minor quality degradation vs full-precision models in edge cases","Completion quality degrades if context window is too small or lacks sufficient surrounding code","May generate syntactically valid but semantically incorrect code without explicit type checking","No real-time validation against Solidity compiler; generated code must be tested","Cannot understand project-specific conventions or custom libraries without explicit examples in context","Explanations may miss subtle security vulnerabilities or edge cases","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.35,"ecosystem":0.24,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.35,"quality":0.2,"ecosystem":0.1,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:24.483Z","last_scraped_at":"2026-05-03T15:20:45.776Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=alfredpros-codellama-7b-instruct-solidity","compare_url":"https://unfragile.ai/compare?artifact=alfredpros-codellama-7b-instruct-solidity"}},"signature":"O6q7T13VtQxiumZVijSW6XF6JbYWYc6k0zy1cuMJ5Nq8O2QCipfhans44wml68aiKiBRHTvh/QSRZ9BRT4/KDg==","signedAt":"2026-06-21T00:32:22.683Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/alfredpros-codellama-7b-instruct-solidity","artifact":"https://unfragile.ai/alfredpros-codellama-7b-instruct-solidity","verify":"https://unfragile.ai/api/v1/verify?slug=alfredpros-codellama-7b-instruct-solidity","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}