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u/bysismo

r/deeplearning r/ollama r/Python r/kaggle r/datasets r/ChromeExtension r/FirefoxAddons r/MachineLearningJobs r/huggingface
▲ 0 r/Python

[Project] Open-sourced a 335K+ Python Expert Instruction Dataset with Modular Token Tiers 🐍🚀

Hello everyone,

We have open-sourced a comprehensive Python instruction-tuning dataset designed for LLM fine-tuning and code generation benchmarks.

As part of a larger 23-category curriculum roadmap, this release covers 8 specialized software engineering domains spanning 335,286

verified examples.

📦 Key Highlights:

• 8 Engineering Domains: Core Python, Data Structures, OOP (SOLID & Dunder protocols), File I/O, Database & ORM, Shell Integration,

Functional Programming, and Algorithms.

• 4 Modular Token Tiers: Pre-bundled into <=128T, <=256T, <=386T, and <=512T ranges to fit different context windows.

• Quality Assurance: All Python code snippets are verified with AST (ast.parse) syntax validation and include self-correction error-

debugging pairs.

Links to explore:

🔗 Kaggle: https://www.kaggle.com/datasets/hakanttkar/turkish-python-expert-instruction-dataset-335k

🔗 Hugging Face: https://huggingface.co/datasets/bysismo/Turkish-Python-instruction-335k

We’d love to hear your feedback, thoughts, or suggestions!

reddit.com
u/bysismo — 3 days ago
▲ 1 r/kaggle

[Dataset] 335K+ High-Quality Turkish Python Expert Instruction Dataset (Modular Token Tiers &amp; 8 Engineering Categories) 🇹🇷🐍

Hey everyone!

As part of our grand curriculum roadmap (target: 1.15M examples across 23 domains), we've officially published the first 8 completed

engineering categories spanning 335,286 high-quality Turkish Python instruction-tuning examples on both Kaggle and Hugging Face.

💡 Why did we build this?

Most open-weights LLMs struggle with non-English programming instructions and technical reasoning. This dataset is engineered to teach

models clean Python 3.10+ syntax, PEP-8 standards, and deep technical explanations natively in Turkish.

📦 Key Highlights:

• 8 Specialized Categories: Python Core, Data Structures, OOP, File I/O, Database/ORM, Shell & System Automation, Functional

Programming, and Algorithms.

• 4 Golden Token Tiers: Pre-bundled into <=128, <=256, <=386, and <=512 token ranges for memory-efficient training.

• Quality Control: Verified via automated AST parsing and live syntax validation.

Feel free to check it out for your multilingual fine-tuning runs or benchmarking:

🔗 Kaggle: https://www.kaggle.com/datasets/hakanttkar/turkish-python-expert-instruction-dataset-335k

🔗 Hugging Face: https://huggingface.co/datasets/bysismo/Turkish-Python-instruction-335k

Feedback and contributions are always welcome!

reddit.com
u/bysismo — 3 days ago
▲ 13 r/huggingface+3 crossposts

[Dataset] Major Update: 0.5M (450K+) Turkish Python Instruction Dataset for LLM Fine-Tuning 🚀

Hey everyone!

Quick update on our open-source initiative: We just bumped our Turkish Python Instruction Dataset from 210K to over 448,000+ unique

samples (0.5M release)! 🚀

HuggingFace Link: https://huggingface.co/datasets/bysismo/Turkish-Python-instruction-450k

### What's included in this release:

• 448,531+ Unique Single-Turn Pairs (Clean ChatML / Alpaca format)

• Categories Covered:

• 🐍 PY_CORE: 205K+ samples (Syntax, built-ins, core logic)

• 🧬 OOP: 49K+ samples (Classes, inheritance, design patterns)

• 🏗️ DATA_STRUCTURES: 44K+ samples (Lists, dicts, custom data structures)

• ⚙️ ALGORITHMS: (In production, rolling out soon!)

### Roadmap & Upcoming Updates:

We are taking a modular, phased release approach. Over the next few weeks, we will roll out token-bucketed splits (128, 256, 386, 512 max

tokens) and dedicated domain packs (FastAPI, Async, DB/ORM, Concurrency, Security, etc.).

### Quick Start:

from datasets import load_dataset

dataset = load_dataset("bysismo/Turkish-Python-instruction-450k", data_files="original_488k.jsonl")

Feedback and ablation results are highly welcome!

u/bysismo — 4 days ago
▲ 2 r/FirefoxAddons

TabNap - Stop wasting memory on idle tabs! Smart suspension, zombie detection, resource ▸ 1 more done monitoring, and 10 languages. Lightweight, privacy-first, and open source.

TabNap is a lightweight, privacy-focused Firefox extension that automatically suspends inactive tabs to free up memory and CPU resources. It helps you browse faster by managing your tabs efficiently.

For FireFox : https://addons.mozilla.org/tr/firefox/addon/tabnap/

  • Automatically suspends tabs after a configurable timeout (5 min to unlimited)
  • Supports manual suspension via toolbar button or context menu
  • Suspend all tabs, current tab, or tabs to the left/right
  • Startup suspension with configurable delay (1-10 seconds)
  • Tab prioritization system based on visit frequency, bookmarks, and usage patterns
  • Detects "zombie" tabs that consume resources despite being idle
  • 4 protection modes: Low, Medium, High, and Stealth
  • Automatic domain banning for resource-heavy sites (500+ requests)
  • Smart filter system with protected sites whitelist (YouTube, Google)
  • Case-insensitive domain matching for reliable filtering
  • Real-time tracking of tab activity and data usage
  • Sub-domain activity visualization with bar charts
  • Top consumers ranking with visual bars
  • Live activity ticker
  • Tracks memory savings with 7-day history
  • Daily and total savings statistics
  • Automatic memory usage alerts at 80%+
  • Save and restore tab sessions
  • Auto-save sessions every 5 minutes
  • Export/import sessions as JSON
  • Up to 20 saved sessions with 100 tabs each
  • Learns your browsing patterns over time
  • Tracks peak activity hours
  • Suggests optimal protection mode based on usage
  • Domain visit frequency tracking
  • 10 languages: Turkish, English, Azerbaijani, German, French, Spanish, Russian, Chinese, Japanese, Arabic
  • Easy language switching from the popup
  • No data collection or transmission
  • All processing happens locally in your browser
  • Open source and transparent
  • Uses Firefox's built-in tabs.discard() API for efficient suspension
  • 3 fallback suspension methods for maximum reliability
  • Background service worker for minimal resource usage
  • Context menu integration for quick actions
  • Custom modal dialogs (no native browser prompts)
  • XSS-protected DOM manipulation
  • Proper error handling throughout
u/bysismo — 9 days ago
▲ 3 r/ChromeExtension

TabNap - Stop wasting memory on idle tabs! Smart suspension, zombie detection, resource ▸ 1 more done monitoring, and 10 languages. Lightweight, privacy-first, and open source. TabNap is a lightweight, privacy-focused Firefox extension that automatically suspends inactive tabs to free up memory and

For Google Chroma : https://chromewebstore.google.com/detail/kdbljejfloiajkneekpanjgcilemeblj?utm_source=item-share-cb

For FireFox : https://addons.mozilla.org/tr/firefox/addon/tabnap/

Automatically suspends tabs after a configurable timeout (5 min to unlimited)

Supports manual suspension via toolbar button or context menu

Suspend all tabs, current tab, or tabs to the left/right

Startup suspension with configurable delay (1-10 seconds)

Tab prioritization system based on visit frequency, bookmarks, and usage patterns

Detects "zombie" tabs that consume resources despite being idle

4 protection modes: Low, Medium, High, and Stealth

Automatic domain banning for resource-heavy sites (500+ requests)

Smart filter system with protected sites whitelist (YouTube, Google)

Case-insensitive domain matching for reliable filtering

Real-time tracking of tab activity and data usage

Sub-domain activity visualization with bar charts

Top consumers ranking with visual bars

Live activity ticker

Tracks memory savings with 7-day history

Daily and total savings statistics

Automatic memory usage alerts at 80%+

Save and restore tab sessions

Auto-save sessions every 5 minutes

Export/import sessions as JSON

Up to 20 saved sessions with 100 tabs each

Learns your browsing patterns over time

Tracks peak activity hours

Suggests optimal protection mode based on usage

Domain visit frequency tracking

10 languages: Turkish, English, Azerbaijani, German, French, Spanish, Russian, Chinese, Japanese, Arabic

Easy language switching from the popup

No data collection or transmission

All processing happens locally in your browser

Open source and transparent

Uses Firefox's built-in tabs.discard() API for efficient suspension

3 fallback suspension methods for maximum reliability

Background service worker for minimal resource usage

Context menu integration for quick actions

Custom modal dialogs (no native browser prompts)

XSS-protected DOM manipulation

Proper error handling throughout

u/bysismo — 10 days ago