KO | EN

GitLite

Minimalist Open Source Repository Search Engine

gitlite — search

#dsh #dsh-plugin #developer-tools #ai-agent #claude-code #codex #typescript #ai-agents #deepseek-harness #mcp #cli #rust

Kontext-Bench-Analysis

★ 29 Open GitHub ↗

No description available.

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Analysis Script and Data Source Overview

This document provides an overview of the analysis script created to process the `metadata.jsonl` file and the context of the data source.

## Data Source: Kontext Bench

The data used for this analysis originates from the [Kontext Bench dataset](https://huggingface.co/datasets/black-forest-labs/kontext-bench). This dataset is a collection of instructions, likely used for training or evaluating language models, particularly in tasks involving image generation or manipulation based on textual prompts.

## Analysis Script: `analysis_instructions.py`

The Python script `analysis_instructions.py` was developed to perform a preliminary analysis of the `metadata.jsonl` file. Its primary goal is to understand the frequency and basic structure of the instructions within the dataset. This is a limited attempt to gain insights into the nature of the training data for the Kontext model.

### Key functionalities of the script:

*   **Data Loading:** Reads and parses the `metadata.jsonl` file, extracting instructions.
*   **Text Preprocessing:** Cleans the instruction text by converting to lowercase, removing punctuation, and tokenizing words.
*   **Frequency Analysis:** Calculates the frequency of individual words, bigrams (pairs of words), and trigrams (sequences of three words).
*   **Structure Analysis:** Identifies common starting words (verbs) used in the instructions.
*   **Output Generation:** Summarizes the findings in a markdown file (`analysis.md`), detailing the most frequent words, bigrams, trigrams, and common instruction structures.

### Analysis Insights (from `analysis.md`):

*   **Most Frequent Words:** Words like 'the', 'a', 'this', 'is', 'make', 'remove', 'add', 'turn' appear frequently, indicating common actions and entities in the instructions.
*   **Common Bigrams & Trigrams:** Phrases such as 'is now', 'of a', 'in the', 'remove the', 'turn this into', and 'this into a' suggest common patterns in how instructions are phrased.
*   **Instruction Starters:** The analysis shows that instructions often begin with verbs like 'make', 'remove', 'turn', 'add', and 'change'.

This analysis provides a basic understanding of the instruction patterns in the Kontext Bench dataset. More advanced Natural Language Processing (NLP) techniques could be employed for a deeper structural and semantic analysis.

*   Full Analysis: https://github.com/lrzjason/Kontext-Bench-Analysis/blob/main/analysis.md

Kontext-Bench-Analysis

Explore Similar Repositories

Was this content helpful?

Recent Feedback

Download README