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README.md
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library_name: transformers
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tags:
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- code
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language:
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- en
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Solidity Llama 3 is a Large Language Model specifically designed for Solidity code completion and infilling. It's based on the LLAMA-3 8b model and has been further trained on the DISL dataset, which contains a large and diverse collection of real-world Solidity smart contracts that have been deployed to Ethereum mainnet. The model is intended to be used for tasks such as code completion within code editors, and users should be aware of its limitations based on its training data and the inherent limitations of the technology.
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- **Developed by:** [More Information Needed]
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- **Model type:** Code Completion
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- **Language(s) (NLP):** Solidity
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- **License:** [More Information Needed]
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- **Finetuned from model:** LLAMA-3 8b
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### Model Sources
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- **Repository:** [More Information Needed]
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- **Demo:** [More Information Needed]
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## Uses
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### Direct Use
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## Bias, Risks, and Limitations
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The model's performance may be affected by biases in the training data, and users should be aware of these limitations. More information is needed for further recommendations.
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library_name: transformers
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tags:
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- code
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- solidity
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language:
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- en
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---
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Solidity Llama 3 is a Large Language Model specifically designed for Solidity code completion and infilling. It's based on the LLAMA-3 8b model and has been further trained on the DISL dataset, which contains a large and diverse collection of real-world Solidity smart contracts that have been deployed to Ethereum mainnet. The model is intended to be used for tasks such as code completion within code editors, and users should be aware of its limitations based on its training data and the inherent limitations of the technology.
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- **Model type:** Code Completion
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- **License:** [More Information Needed]
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- **Finetuned from model:** LLAMA-3 8b
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## Uses
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### Direct Use
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## Bias, Risks, and Limitations
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The model's performance may be affected by biases in the training data, and users should be aware of these limitations. More information is needed for further recommendations.
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