bendalenda/security-analyst-ai
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kTool Calling:SupportedPublished:May 31, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The bendalenda/security-analyst-ai is an 8 billion parameter Llama 3 model, developed by bendalenda, and fine-tuned from unsloth/llama-3-8b-bnb-4bit. This model is optimized for security analysis tasks, leveraging its 8192-token context length to process and interpret security-related information. It was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning.
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bendalenda/security-analyst-ai Overview
The bendalenda/security-analyst-ai is an 8 billion parameter language model, fine-tuned by bendalenda. It is based on the Llama 3 architecture, specifically fine-tuned from the unsloth/llama-3-8b-bnb-4bit model. This model was developed with a focus on applications within the security analysis domain.
Key Characteristics
- Model Size: 8 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Features an 8192-token context window, suitable for processing moderately long security logs, reports, or incident details.
- Training Methodology: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- License: Distributed under the Apache-2.0 license, allowing for broad use and modification.
Good For
- Security Analysis: Designed for tasks related to security, such as threat intelligence, vulnerability assessment, or incident response support.
- Research and Development: Provides a base for further experimentation and fine-tuning on specific security datasets.
- Efficient Deployment: The use of Unsloth for training suggests potential for optimized inference, making it suitable for applications where speed is a factor.