saranshankar/llama-3.2-3b-classification-merged
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kPublished:May 29, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The saranshankar/llama-3.2-3b-classification-merged model is an 8 billion parameter Llama-3 based language model, fine-tuned by saranshankar. It was trained using Unsloth and Huggingface's TRL library for accelerated fine-tuning. This model is specifically designed for classification tasks, leveraging its Llama-3 architecture for efficient performance.
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Model Overview
The saranshankar/llama-3.2-3b-classification-merged is an 8 billion parameter Llama-3 based language model, developed by saranshankar. It was fine-tuned from unsloth/llama-3-8b-Instruct-bnb-4bit using the Unsloth library in conjunction with Huggingface's TRL library, which enabled a 2x faster training process.
Key Capabilities
- Llama-3 Architecture: Built upon the robust Llama-3 foundation, providing strong language understanding capabilities.
- Accelerated Fine-tuning: Benefits from Unsloth's optimization for faster training, making it efficient for custom applications.
- Classification Focus: Specifically fine-tuned for classification tasks, suggesting optimized performance in categorizing data.
Good For
- Classification Applications: Ideal for developers requiring a Llama-3 based model for various text classification needs.
- Efficient Deployment: Its 8 billion parameter size, combined with efficient fine-tuning, makes it suitable for applications where resource optimization is important.