ccibeekeoc42/Llama-3.2-8B-Instruct-bnb-4bit_merged_16bit_finetune_2025-03-07

TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Mar 7, 2025License:apache-2.0Architecture:Transformer Open Weights Cold

The ccibeekeoc42/Llama-3.2-8B-Instruct-bnb-4bit_merged_16bit_finetune_2025-03-07 is an 8 billion parameter Llama-based instruction-tuned language model, fine-tuned by ccibeekeoc42. This model was trained 2x faster using Unsloth and Huggingface's TRL library, building upon the Llama3.1-8b-instruct-SFT-2024-11-09 base. It is designed for general instruction-following tasks, leveraging efficient training methodologies.

Loading preview...

Overview

This model, developed by ccibeekeoc42, is an 8 billion parameter instruction-tuned variant of the Llama 3.2 architecture. It was fine-tuned from the ccibeekeoc42/Llama3.1-8b-instruct-SFT-2024-11-09 base model. A key differentiator is its training efficiency, having been trained 2x faster using the Unsloth library in conjunction with Huggingface's TRL library.

Key Capabilities

  • Instruction Following: Designed to accurately follow user instructions for various natural language tasks.
  • Efficient Training: Benefits from optimized training techniques, allowing for faster iteration and deployment.
  • Llama Architecture: Inherits the robust capabilities and general-purpose utility of the Llama family of models.

Good For

  • Developers seeking an instruction-tuned Llama model with an 8 billion parameter count.
  • Applications requiring a balance of performance and computational efficiency, particularly those leveraging Unsloth's optimizations.
  • General natural language understanding and generation tasks where instruction adherence is critical.