nethmid/llama3.2.3B_cognitive_distortions_16bit
The nethmid/llama3.2.3B_cognitive_distortions_16bit model is a 3.2 billion parameter Llama-3.2-3B-Instruct variant developed by nethmid. This model was fine-tuned using Unsloth and Huggingface's TRL library, resulting in faster training. It is designed for tasks related to cognitive distortions, leveraging its Llama architecture for specialized applications.
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Model Overview
This model, developed by nethmid, is a fine-tuned variant of the Llama-3.2-3B-Instruct architecture, featuring 3.2 billion parameters. It was specifically trained using the Unsloth framework and Huggingface's TRL library, which enabled a significantly faster training process.
Key Characteristics
- Base Model: Fine-tuned from unsloth/Llama-3.2-3B-Instruct.
- Training Efficiency: Leverages Unsloth for 2x faster training.
- Parameter Count: 3.2 billion parameters.
- Context Length: Supports a context length of 32768 tokens.
Primary Focus
This model is specialized for applications involving cognitive distortions. Its fine-tuning aims to enhance its performance and understanding in this specific domain, making it suitable for tasks requiring nuanced interaction with such concepts.
Licensing
The model is released under the Apache-2.0 license, allowing for broad use and distribution.