sargevinix/archai-v1-merged
sargevinix/archai-v1-merged is a 12 billion parameter Mistral-based causal language model developed by sargevinix, fine-tuned from unsloth/mistral-nemo-instruct-2407-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning. With a 32768 token context length, it is optimized for efficient performance on tasks typically handled by Mistral-family models.
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Model Overview
sargevinix/archai-v1-merged is a 12 billion parameter language model, fine-tuned by sargevinix. It is based on the Mistral architecture, specifically fine-tuned from the unsloth/mistral-nemo-instruct-2407-bnb-4bit model. A key characteristic of this model's development is its training methodology, which leveraged Unsloth and Huggingface's TRL library to achieve a 2x speedup in the fine-tuning process.
Key Characteristics
- Architecture: Mistral-based, fine-tuned from
unsloth/mistral-nemo-instruct-2407-bnb-4bit. - Parameter Count: 12 billion parameters.
- Context Length: Supports a substantial context window of 32768 tokens.
- Training Efficiency: Fine-tuned with Unsloth, resulting in significantly faster training times.
- License: Released under the Apache-2.0 license.
Potential Use Cases
This model is suitable for applications requiring a Mistral-family model with a large context window, where efficient fine-tuning was a priority during development. Its foundation suggests capabilities for general language understanding and generation tasks, benefiting from the Mistral architecture's known performance characteristics.