kairawal/Llama-3.2-3B-Instruct-ES-SynthDolly-r16alpha128-E8-S73
TEXT GENERATIONConcurrency Cost:1Model Size:3.2BQuant:BF16Ctx Length:32kPublished:May 23, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The kairawal/Llama-3.2-3B-Instruct-ES-SynthDolly-r16alpha128-E8-S73 is a 3.2 billion parameter instruction-tuned Llama model developed by kairawal. It was fine-tuned using Unsloth and Huggingface's TRL library, resulting in a faster training process. This model is designed for instruction-following tasks, leveraging its Llama architecture and efficient fine-tuning methodology.
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Model Overview
The kairawal/Llama-3.2-3B-Instruct-ES-SynthDolly-r16alpha128-E8-S73 is an instruction-tuned Llama model with 3.2 billion parameters. It was developed by kairawal and fine-tuned from the unsloth/llama-3.2-3b-Instruct base model.
Key Characteristics
- Architecture: Based on the Llama model family.
- Parameter Count: 3.2 billion parameters, making it a relatively compact yet capable model.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.
- Instruction-Tuned: Optimized for understanding and following instructions, making it suitable for various conversational and task-oriented applications.
Potential Use Cases
- Instruction Following: Ideal for applications requiring the model to respond accurately to user prompts and instructions.
- Resource-Efficient Deployment: Its 3.2 billion parameter size, combined with efficient training, suggests potential for deployment in environments with moderate computational resources.
- Experimental Fine-tuning: Demonstrates the effectiveness of Unsloth for accelerating the fine-tuning of Llama models.