mauricioobgo/llama-2-7b-resume-mauricioobgo
TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kLicense:mitArchitecture:Transformer Open Weights Cold
The mauricioobgo/llama-2-7b-resume-mauricioobgo model is a Llama 2-based language model fine-tuned by mauricioobgo. This model is specifically trained on the mauricioobgo/resume-qa-data-2023-10 dataset. It is designed for question-answering tasks related to resumes, aiming for high accuracy in this specialized domain.
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Overview
This model, mauricioobgo/llama-2-7b-resume-mauricioobgo, is a specialized language model built upon the Llama 2 architecture. It has been fine-tuned by mauricioobgo with a specific focus on resume-related question answering.
Key Capabilities
- Resume-specific QA: The model is trained on the
mauricioobgo/resume-qa-data-2023-10dataset, making it proficient in understanding and answering questions based on resume content. - Accuracy-focused: The primary metric for this model is accuracy, indicating its design goal to provide precise answers within its domain.
Good For
- Automated resume screening: Ideal for systems that need to extract specific information or answer questions from resumes programmatically.
- HR technology applications: Can be integrated into tools for candidate evaluation, skill matching, or data extraction from CVs.
- Specialized information retrieval: Useful for applications requiring high accuracy in question answering over structured or semi-structured textual data like resumes.