wooodpecker22/icp-assistant-model
The wooodpecker22/icp-assistant-model is an 8 billion parameter Llama 3.1-based instruction-tuned language model developed by wooodpecker22. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is designed for general instruction-following tasks, leveraging the Llama 3.1 architecture for robust performance.
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Model Overview
The wooodpecker22/icp-assistant-model is an 8 billion parameter instruction-tuned language model, developed by wooodpecker22. It is based on the Llama 3.1 architecture, specifically fine-tuned from unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit.
Key Characteristics
- Architecture: Llama 3.1-based, 8 billion parameters.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- License: Distributed under the Apache-2.0 license.
Intended Use Cases
This model is suitable for a variety of general instruction-following applications, benefiting from the Llama 3.1 foundation and optimized fine-tuning. Its efficient training process suggests a focus on practical deployment and performance for common NLP tasks.