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README.md

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-# Mass Evaluations
-
-Simple benchmark tool for running predefined prompts through all checkpoints of a model.
-
-## Usage
-
-```bash
-python benchmark.py [model_name] [options]
-```
-
-## Examples
-
-```bash
-# Benchmark all checkpoints of a model
-python benchmark.py pico-decoder-tiny-dolma5M-v1
-
-# Specify custom output directory
-python benchmark.py pico-decoder-tiny-dolma5M-v1 --output my_results/
-
-# Use custom prompts file
-python benchmark.py pico-decoder-tiny-dolma5M-v1 --prompts my_prompts.json
-```
-
-## Managing Prompts
-
-Prompts are stored in `prompts.json` as a simple array of strings:
-
-```json
-[
-  "Hello, how are you?",
-  "Complete this story: Once upon a time",
-  "What is the capital of France?"
-]
-```
-
-### Adding New Prompts
-
-Simply edit `prompts.json` and add new prompt strings to the array. Super simple!
-
-## Features
-
-- **Auto-discovery**: Finds all `step_*` checkpoints automatically
-- **JSON-based prompts**: Easily customizable prompts via JSON file
-- **Readable output**: Markdown reports with clear structure
-- **Error handling**: Continues on failures, logs errors
-- **Progress tracking**: Shows real-time progress
-- **Metadata logging**: Includes generation time and parameters
-
-## Output
-
-Results are saved as markdown files in `results/` directory:
-```
-results/
-├── pico-decoder-tiny-dolma5M-v1_benchmark_20250101_120000.md
-├── pico-decoder-tiny-dolma29k-v3_benchmark_20250101_130000.md
-└── ...
-```
-
-## Predefined Prompts
-
-1. "Hello, how are you?" (conversational)
-2. "Complete this story: Once upon a time" (creative)
-3. "Explain quantum physics in simple terms" (explanatory)
-4. "Write a haiku about coding" (creative + structured)
-5. "What is the capital of France?" (factual)
-6. "The meaning of life is" (philosophical)
-7. "In the year 2050," (futuristic)
-8. "Python programming is" (technical)