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| title: AutoGrader | |
| emoji: 🧠 | |
| colorFrom: indigo | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 6.3.0 | |
| app_file: app.py | |
| pinned: false | |
| # AutoGrader | |
| AutoGrader is a **CPU-only, LLM-based academic grading system** that evaluates student submissions using a provided **question paper and rubric**, while also awarding marks for **logically correct alternative solutions**. | |
| ## Key Features | |
| - Runs entirely on **CPU** (Hugging Face Spaces compatible) | |
| - **Rubric-aware** grading with flexibility for alternative correct answers | |
| - **Prompt-controlled evaluation** (e.g. grade only Q2, grade Q2 & Q4, custom marks) | |
| - **Multiple model options** (user-selectable) | |
| - **Less deterministic grading** via controlled sampling | |
| - **Structured JSON output** for reliable parsing | |
| - Works via **Hugging Face API** (can be called from Kaggle or other platforms) | |
| ## Supported Models | |
| - Phi-3-mini (fast, CPU-friendly) | |
| - Mistral-7B-Instruct (higher quality, slower on CPU) | |
| Model weights are **not stored in this repository** and are automatically downloaded from the Hugging Face Hub at runtime. | |
| ## How It Works | |
| 1. The student submission is first analyzed to extract key ideas. | |
| 2. A second evaluation step grades the answer using the rubric and grading instructions. | |
| 3. Marks are assigned fairly, even for solutions not explicitly listed in the rubric. | |
| 4. Output is returned as **strict JSON**. | |
| ## Input Fields | |
| - **Question Paper** | |
| - **Rubric** | |
| - **Grading Instruction** | |
| Example: | |
| `Grade only Question 2 out of 20 marks` | |
| - **Student Submission** | |
| ## Output | |
| A structured JSON containing: | |
| - Total marks | |
| - Per-question marks | |
| - Short justification | |
| ## Limitations | |
| - CPU-only inference means **higher latency** for larger models | |
| - LLM-based grading is **not fully deterministic** | |
| - Designed for academic assistance, not high-stakes automated grading without review | |
| ## License & Usage | |
| This project uses open-source models from the Hugging Face Hub. | |
| Please ensure model licenses are respected when deploying or redistributing. | |
| --- | |
| Built for flexible, research-oriented automated assessment. | |