xammi/MunicipalPredictionModel-Llama3
The xammi/MunicipalPredictionModel-Llama3 is an 8 billion parameter Llama-based language model developed by xammi, fine-tuned from xammi/municipal-prediction-merged-llama-model-v1.0. This model was trained using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for municipal prediction tasks, leveraging its Llama3 architecture and 32768 token context length.
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Model Overview
The xammi/MunicipalPredictionModel-Llama3 is an 8 billion parameter Llama-based language model developed by xammi. It was fine-tuned from the xammi/municipal-prediction-merged-llama-model-v1.0 base model.
Key Characteristics
- Architecture: Based on the Llama3 family of models.
- Parameter Count: Features 8 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, allowing for processing longer inputs and maintaining conversational coherence over extended interactions.
- Training Efficiency: The model's training process leveraged Unsloth and Huggingface's TRL library, which facilitated a 2x faster training speed.
Primary Use Case
This model is specifically designed and fine-tuned for municipal prediction tasks. Its specialized training makes it suitable for applications requiring analysis and forecasting related to municipal data and operations. The Apache-2.0 license allows for broad usage and modification.