Model Overview
This model, zkaedi/gemma-7b-solidity-energy-signatures, is a fine-tuned version of Google's Gemma-2-9B architecture, featuring 9 billion parameters and a context length of 16384 tokens. It has been specifically adapted for specialized tasks, likely within the domain of Solidity smart contracts and energy signature analysis, although the exact training data specifics are not detailed in the provided README.
Key Characteristics
- Base Model: Fine-tuned from
google/gemma-2-9b. - Training Framework: Utilizes the TRL library for supervised fine-tuning (SFT).
- Parameter Count: 9 billion parameters.
- Context Length: Supports a substantial context of 16384 tokens.
Potential Use Cases
Given its fine-tuning, this model is likely optimized for:
- Solidity Code Analysis: Assisting with understanding, generating, or debugging Solidity smart contracts.
- Blockchain Security: Identifying patterns or anomalies related to "energy signatures" in blockchain transactions or smart contract execution.
- Specialized Development: Supporting developers working on projects requiring deep understanding of Solidity and related on-chain data.
Training Details
The model underwent Supervised Fine-Tuning (SFT). The training leveraged specific versions of key frameworks:
- PEFT: 0.18.1
- TRL: 0.29.0
- Transformers: 5.0.0
- Pytorch: 2.10.0+cu128
- Datasets: 4.0.0
- Tokenizers: 0.22.2