lakshyaixi/Llama_3_2_3B_DPO_v18_220626
TEXT GENERATIONConcurrent Unit Cost:1Model Size:3.2BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jun 22, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
lakshyaixi/Llama_3_2_3B_DPO_v18_220626 is a 3.2 billion parameter Llama 3 model developed by lakshyaixi, fine-tuned using DPO. This model was trained 2x faster with Unsloth and Huggingface's TRL library, making it efficient for various language generation tasks. It is suitable for applications requiring a compact yet capable language model.
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Model Overview
lakshyaixi/Llama_3_2_3B_DPO_v18_220626 is a 3.2 billion parameter Llama 3 model, developed by lakshyaixi. It has been fine-tuned using Direct Preference Optimization (DPO) from the base model lakshyaixi/Llama_3_2_3B_DPO_v18_refined.
Key Characteristics
- Efficient Training: This model was trained significantly faster, achieving a 2x speedup, by leveraging Unsloth and Huggingface's TRL library. This indicates an optimized training process for resource efficiency.
- DPO Fine-tuning: The use of DPO suggests an emphasis on aligning the model's outputs with human preferences, potentially leading to more helpful and harmless responses.
- Compact Size: With 3.2 billion parameters, it offers a balance between performance and computational requirements, making it suitable for deployment in environments with limited resources.
Potential Use Cases
- Text Generation: Generating coherent and contextually relevant text for various applications.
- Chatbots and Conversational AI: Its DPO fine-tuning can contribute to more natural and preferred conversational flows.
- Edge Device Deployment: The smaller parameter count makes it a candidate for deployment on devices with constrained memory and processing power.