kairawal/Llama-3.2-3B-Instruct-EL-SynthDolly-r16alpha32-E3-S73

TEXT GENERATIONConcurrency Cost:1Model Size:3.2BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:May 14, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The kairawal/Llama-3.2-3B-Instruct-EL-SynthDolly-r16alpha32-E3-S73 is a 3.2 billion parameter instruction-tuned language model, developed by kairawal and finetuned from unsloth/llama-3.2-3b-Instruct. This model was optimized for faster training using Unsloth and Huggingface's TRL library. It is designed for general instruction-following tasks, leveraging its efficient training methodology for practical applications. Its compact size and optimized training make it suitable for environments requiring efficient deployment.

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Overview

The kairawal/Llama-3.2-3B-Instruct-EL-SynthDolly-r16alpha32-E3-S73 is a 3.2 billion parameter instruction-tuned language model. It was developed by kairawal and is based on the unsloth/llama-3.2-3b-Instruct architecture. A key differentiator for this model is its training methodology: it was finetuned using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process.

Key Capabilities

  • Efficient Training: Leverages Unsloth for significantly faster finetuning compared to standard methods.
  • Instruction Following: Designed to respond effectively to a wide range of user instructions.
  • Compact Size: At 3.2 billion parameters, it offers a balance between performance and computational efficiency.
  • Llama-3.2 Base: Benefits from the underlying architecture of the Llama-3.2 series.

Good For

  • Rapid Prototyping: Its efficient training makes it suitable for quick iteration and development cycles.
  • Resource-Constrained Environments: The 3.2B parameter count allows for deployment in settings with limited computational resources.
  • General Instruction-Following: Can be used for various tasks requiring a model to understand and execute commands.
  • Experimentation with Unsloth: Ideal for developers looking to utilize and evaluate the benefits of Unsloth's accelerated training.