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| title: ResumeAnalyzer Mistral 7b Mangesh | |
| emoji: 🏃 | |
| colorFrom: pink | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 5.23.1 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| short_description: A Resume Analyzer For an JobSeeker | |
| hf_oauth: true | |
| hf_oauth_scopes: | |
| - inference-api | |
| # Resume Analyzer App | |
| # Resume Analyzer App | |
| ## Overview | |
| The **Resume Analyzer App** is a powerful tool designed to evaluate and rank resumes based on their fit for a specific job. Ideal for recruiters screening candidates or job seekers refining their applications, this app scores resumes out of 100 using a data-driven approach. By comparing resumes to a provided job description, it delivers actionable insights to identify the best candidates or improve resume quality. | |
| ## Key Features | |
| - **Job-Specific Analysis**: Evaluates resumes by comparing them to a user-provided job description. | |
| - **Scoring Parameters**: | |
| - Relevance to Job | |
| - Experience Quality | |
| - Skills Match | |
| - Education & Certifications | |
| - Achievements & Impact | |
| - Clarity & Professionalism | |
| - Customization | |
| - **Detailed Feedback**: Provides a total score and breakdown by parameter, highlighting strengths and areas for improvement. | |
| - **Flexible Weighting**: Adjusts scoring weights based on job type (e.g., emphasizing skills for tech roles). | |
| - **Tech-Powered**: Built with Python, leveraging NLP (spaCy/NLTK), PDF parsing (PyPDF2/pdfplumber), and regex for robust analysis. | |
| ## How It Works | |
| 1. **Input**: Upload a resume (PDF or text) and a job description. | |
| 2. **Analysis**: The app extracts text, processes it with NLP, and scores it across defined parameters. | |
| 3. **Output**: Get a total score (e.g., 82/100) and a detailed breakdown (e.g., Skills: 14/15, Experience: 18/20). | |
| 4. **Ranking**: Compare multiple resumes to find the best fit for the job. | |
| ## Use Cases | |
| - **Recruiters**: Quickly filter top candidates for a role. | |
| - **Job Seekers**: Optimize your resume for a specific job posting. | |
| - **Educators**: Teach students how to tailor resumes with data-backed feedback. | |
| ## Example | |
| **Software Engineer Role**: | |
| Score: 85/100 | |
| Relevance: 18/20, Skills: 14/15, Experience: 16/20, Clarity: 9/10, Customization: 8/10 | |
| ## Why Use It? | |
| - Saves time by automating resume screening. | |
| - Provides objective, job-specific evaluations. | |
| - Adapts to any industry or role with flexible scoring. | |
| ## 📜 License | |
| **Your code** is licensed under the [MIT License](LICENSE). | |
| Note: This Space uses external models (Mistral-7B) under their own licenses. |