EpistemeAI/Llama-3.2-3B-Agent007-Coder
EpistemeAI/Llama-3.2-3B-Agent007-Coder is a 3.21 billion parameter Llama 3.2-based model developed by EpistemeAI, fine-tuned for agentic and coding tasks. It leverages the Llama 3.2 optimized transformer architecture and was further trained with agent datasets, Code Alpaca 20K, and Magpie Ultra 0.1. This model is specifically designed for code generation and agent-like applications, building upon Meta's multilingual Llama 3.2 foundation.
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Model Overview
EpistemeAI/Llama-3.2-3B-Agent007-Coder is a 3.21 billion parameter language model developed by EpistemeAI, fine-tuned from Meta's Llama 3.2-3B-Instruct. It utilizes an optimized transformer architecture and Grouped-Query Attention (GQA) for efficient inference. The model was further trained using agent datasets, Code Alpaca 20K, and Magpie Ultra 0.1, enhancing its capabilities in specific domains.
Key Capabilities
- Code Generation: Enhanced through fine-tuning on the Code Alpaca 20K dataset.
- Agentic Applications: Optimized for tasks requiring agent-like reasoning and interaction, leveraging agent datasets.
- Multilingual Support: Inherits multilingual capabilities from the base Llama 3.2 model, officially supporting English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.
- Instruction Following: Instruction-tuned for dialogue and assistant-like chat use cases.
Good For
- Code-related tasks: Generating, understanding, or assisting with code.
- Agent-based systems: Developing AI agents for retrieval, summarization, or interactive applications.
- Multilingual chat assistants: Creating chatbots that can operate across several supported languages.
- Research and commercial use: Intended for a broad range of applications under the Llama 3.2 Community License.