Josuef663/advanced_finetune_16bit
TEXT GENERATIONConcurrency Cost:1Model Size:3.2BQuant:BF16Ctx Length:32kPublished:Mar 6, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The Josuef663/advanced_finetune_16bit is a 3.2 billion parameter Llama-based instruction-tuned model developed by Josuef663, fine-tuned from unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, focusing on efficient local training. It serves as a demonstration of local model fine-tuning capabilities on consumer-grade hardware.
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Model Overview
The Josuef663/advanced_finetune_16bit is a 3.2 billion parameter Llama-based instruction-tuned model, developed by Josuef663. It was fine-tuned from the unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit base model.
Key Characteristics
- Architecture: Llama-based, instruction-tuned.
- Parameter Count: 3.2 billion parameters.
- Training Efficiency: Utilizes Unsloth and Huggingface's TRL library for accelerated training.
- Origin: Developed as a personal learning project to demonstrate local fine-tuning on an RTX3060 laptop with 6GB VRAM.
Intended Use Cases
This model is primarily a demonstration of efficient fine-tuning techniques on consumer hardware. It is suitable for:
- Educational Purposes: Learning about local LLM fine-tuning.
- Experimentation: Testing fine-tuning workflows with Unsloth and TRL.
- Resource-Constrained Environments: Exploring LLM capabilities on systems with limited VRAM.