Transformers
Safetensors
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  ## Bias, Risks, and Limitations
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- The training data primarily consists of code from publicly sourced Solidity projects which may not encompass the full diversity of programming styles and techniques used in professional environments. Users should be cautious of potential biases in generated code and always review and test code before use.
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  ### Recommendations
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  ### Training Data
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- The model was trained on a dataset consisting of pairs of natural language instructions and their corresponding Solidity code implementations. This dataset includes over [X examples] from diverse sources aimed at covering a broad range of smart contract functionalities.
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  ### Training Procedure
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  #### Summary
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- Initial evaluations show promising results in generating syntactically correct Solidity code, with further testing planned to assess the semantic accuracy and security implications of the generated contracts.
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  ## Environmental Impact
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  ## Bias, Risks, and Limitations
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+ The training data primarily consists of code from publicly sourced Solidity projects which may not encompass the full diversity of programming styles and techniques.
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  ### Recommendations
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  ### Training Data
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+ The model was trained on a dataset consisting of pairs of natural language instructions and their corresponding Solidity code implementations. This dataset includes over 6000 input and outputs.
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  ### Training Procedure
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  #### Summary
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+ Initial evaluations show promising results in generating Solidity code, with further testing planned.
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  ## Environmental Impact
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