SUBSECT420/Llama3.2-3b-Neuro-sama
TEXT GENERATIONConcurrency Cost:1Model Size:3.2BQuant:BF16Ctx Length:32kPublished:Apr 6, 2025License:apache-2.0Architecture:Transformer0.0K Open Weights Warm
SUBSECT420/Llama3.2-3b-Neuro-sama is a 3.2 billion parameter Llama 3.2-based instruction-tuned model developed by SUBSECT420. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
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Model Overview
SUBSECT420/Llama3.2-3b-Neuro-sama is a 3.2 billion parameter language model, fine-tuned from the unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit base model. Developed by SUBSECT420, this model leverages the Unsloth library in conjunction with Huggingface's TRL library for efficient training.
Key Capabilities
- Efficient Training: Achieves 2x faster training speeds due to the integration of Unsloth.
- Instruction Following: Designed to respond effectively to a variety of instructions, building upon its Llama 3.2 base.
- Compact Size: At 3.2 billion parameters, it offers a balance between performance and computational efficiency.
Good For
- Applications requiring a capable instruction-tuned model with a smaller footprint.
- Scenarios where faster fine-tuning is a critical advantage.
- General natural language understanding and generation tasks.