ubiodee/Cardano_plutus
The ubiodee/Cardano_plutus model is a 3.2 billion parameter language model fine-tuned from Meta's Llama-3.2-3B architecture. With a context length of 32768 tokens, this model is specifically adapted for tasks related to Cardano's Plutus smart contract platform. Its fine-tuning on an unspecified dataset aims to enhance its understanding and generation capabilities within the Plutus ecosystem, making it suitable for developers working with Cardano smart contracts.
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Overview
The ubiodee/Cardano_plutus model is a specialized language model, fine-tuned from the meta-llama/Llama-3.2-3B base architecture. It features 3.2 billion parameters and supports a substantial context length of 32768 tokens, making it capable of processing extensive inputs.
Key Characteristics
- Base Model: Derived from Meta's Llama-3.2-3B, providing a robust foundation.
- Parameter Count: 3.2 billion parameters, balancing performance with computational efficiency.
- Context Length: 32768 tokens, allowing for detailed analysis and generation over long texts.
- Fine-tuning Focus: Specifically fine-tuned for applications within the Cardano Plutus smart contract environment, though the exact dataset used for this specialization is not detailed.
Training Details
The model was trained using the following key hyperparameters:
- Learning Rate: 5e-05
- Optimizer: ADAMW_TORCH
- Epochs: 3
- Batch Size: 1 (with gradient accumulation steps of 4, leading to a total effective batch size of 4)
Intended Use Cases
While specific use cases are not explicitly detailed in the original README, given its fine-tuning on Cardano Plutus, this model is likely intended for tasks such as:
- Assisting with Plutus smart contract development.
- Generating or analyzing Plutus code snippets.
- Understanding and explaining concepts related to the Cardano blockchain and Plutus.
Further information regarding its specific capabilities, limitations, and training data would provide a clearer picture of its optimal applications.