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+# GIMBench
+
+GIMBench is a benchmarking framework for evaluating Guided Infilling Models (GIM).
+
+## Overview
+
+This project provides tools and benchmarks to evaluate models' ability to perform guided infilling tasks - generating text that follows specific constraints and patterns.
+
+## Installation
+
+Install GIMBench using pip:
+
+```bash
+pip install gimbench
+```
+
+For development:
+
+```bash
+make install-dev
+```
+
+## Usage
+
+GIMBench provides several benchmark types:
+
+- **CV Parsing**: Evaluate models on structured information extraction from CVs
+- **Regex Matching**: Test models' ability to generate text matching specific patterns
+- **Multiple Choice QA**: Assess guided generation in question-answering contexts
+- **Perplexity**: Measure language modeling quality with constraints
+
+### Example Commands
+
+Run MMLU-Pro benchmark:
+
+```bash
+python -m gimbench.mcqa.mmlu_pro \
+    --model_type vllm \
+    --model_name meta-llama/Llama-3.1-8B-Instruct \
+    --base_url http://localhost:8000/v1
+```
+
+Run GPQA Diamond benchmark:
+
+```bash
+python -m gimbench.mcqa.gpqa_diamond \
+    --model_type openai \
+    --model_name gpt-4 \
+    --api_key YOUR_API_KEY
+```
+
+Run GIM-SFT perplexity evaluation:
+
+```bash
+python -m gimbench.ppl.gim_sft \
+    --model_type vllm-offline \
+    --model_name meta-llama/Llama-3.1-8B-Instruct
+```
+
+## Development
+
+Run linting:
+
+```bash
+make lint
+```
+
+Fix linting issues automatically:
+
+```bash
+make lint-fix
+```
+
+Run pre-commit hooks:
+
+```bash
+make pre-commit
+```