lakshyaixi/Llama_3_2_3B_Conversational_v6_SFT_10voicebot_interrupt_model
The lakshyaixi/Llama_3_2_3B_Conversational_v6_SFT_10voicebot_interrupt_model is a 3.2 billion parameter Llama-3.2-3B-Instruct model, fine-tuned by lakshyaixi. This model was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. Its primary differentiation lies in its conversational fine-tuning, making it suitable for interactive dialogue applications.
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Overview
This model, developed by lakshyaixi, is a fine-tuned version of the Llama-3.2-3B-Instruct architecture, featuring 3.2 billion parameters and a 32768 token context length. It was specifically fine-tuned for conversational applications, indicating an optimization for dialogue and interactive exchanges.
Key Characteristics
- Base Model: Fine-tuned from unsloth/Llama-3.2-3B-Instruct.
- Training Efficiency: Utilized Unsloth and Huggingface's TRL library for accelerated fine-tuning.
- Parameter Count: 3.2 billion parameters.
- Context Length: Supports a substantial context of 32768 tokens.
Intended Use Cases
This model is particularly well-suited for applications requiring conversational capabilities. Its fine-tuning for dialogue suggests strong performance in:
- Chatbots and virtual assistants.
- Interactive voicebot systems.
- Applications where natural language conversation is a core requirement.