doandune/LexGuard-Mistral-Risk-Merged
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Mar 14, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
LexGuard-Mistral-Risk-Merged is a 7 billion parameter Mistral-based causal language model developed by doandune, fine-tuned from unsloth/mistral-7b-instruct-v0.2-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning. Its primary use case is for applications requiring a Mistral 7B model with efficient training characteristics.
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LexGuard-Mistral-Risk-Merged Overview
LexGuard-Mistral-Risk-Merged is a 7 billion parameter language model developed by doandune, building upon the Mistral architecture. It is fine-tuned from the unsloth/mistral-7b-instruct-v0.2-bnb-4bit base model, leveraging the Unsloth library and Huggingface's TRL for efficient training.
Key Capabilities
- Efficient Fine-tuning: Achieves 2x faster training speeds due to its optimization with Unsloth.
- Mistral 7B Foundation: Inherits the strong general language understanding and generation capabilities of the Mistral 7B Instruct v0.2 model.
- Apache 2.0 License: Provides flexibility for commercial and research use.
Good For
- Developers seeking a Mistral 7B model with a focus on accelerated fine-tuning.
- Applications where efficient resource utilization during training is critical.
- Projects requiring a robust, instruction-tuned base for further specialization.