dante557/HR-Recruiter-Llama-3.1-8B-v1
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kPublished:May 8, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The dante557/HR-Recruiter-Llama-3.1-8B-v1 is an 8 billion parameter Llama 3.1-based language model, developed by dante557. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is specifically designed for HR recruiting tasks, leveraging its Llama 3.1 foundation for specialized applications in this domain.
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Model Overview
The dante557/HR-Recruiter-Llama-3.1-8B-v1 is an 8 billion parameter language model, fine-tuned from the unsloth/Meta-Llama-3.1-8B-Instruct base model. Developed by dante557, this model leverages the Llama 3.1 architecture, optimized for specific applications.
Key Capabilities
- Specialized Fine-tuning: The model has undergone fine-tuning, indicating a focus on particular use cases beyond general instruction following.
- Efficient Training: Training was accelerated using Unsloth and Huggingface's TRL library, suggesting an efficient development process.
- Llama 3.1 Foundation: Built upon the Meta-Llama-3.1-8B-Instruct, it inherits the strong language understanding and generation capabilities of the Llama 3.1 series.
Good For
- HR Recruiting Tasks: Given its name, the model is specifically tailored for applications within human resources, likely involving tasks such as resume parsing, candidate screening, or generating job descriptions.
- Applications requiring Llama 3.1 base: Users looking for a specialized model built on the Llama 3.1 architecture with an 8192 token context length.
- Developers seeking efficient fine-tuned models: The use of Unsloth implies a focus on performance and resource efficiency during the fine-tuning process.