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Mecellem Models Turkish Models Trained From Scratc

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Implement techniques from Mecellem Models: Turkish Models Trained from Scratch and Continually Pre-trained for the Legal Domain. This paper presents Mecellem models, a framework for developing specialized language models for the Turkish legal domain through domain adaptation strategies

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  • Added September 9, 2026
research

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A100/100

Scanned September 9, 2026

npx -y skills add ADu2021/skillXiv --skill mecellem-models-turkish-models-trained-from-scratc --agent claude-code

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SKILL.md
---
name: mecellem-models-turkish-models-trained-from-scratc
title: "Mecellem Models: Turkish Models Trained from Scratch and Continually Pre-trained for the Legal Domain"
version: 0.0.2
engine: skillxiv-v0.0.2-claude-opus-4.6
license: MIT
url: "https://arxiv.org/abs/2601.16018"
keywords: ["model", "framework"]
description: "Implement techniques from Mecellem Models: Turkish Models Trained from Scratch and Continually Pre-trained for the Legal Domain. This paper presents Mecellem models, a framework for developing specialized language models for the Turkish legal domain through domain adaptation strategies"
---

## Overview

This skill implements concepts from the research paper [[2601.16018](https://arxiv.org/abs/2601.16018)].

## When to Use

- When you need to implement techniques described in this paper
- When working on problems that this research addresses
- When you want to understand the core concepts and methodology

## When NOT to Use

- This skill provides research-level insights; production implementations may require additional engineering
- Some concepts may require significant tuning for specific use cases
- Always evaluate applicability to your specific problem domain

## Key Concepts

The paper addresses: This paper presents Mecellem models, a framework for developing specialized language models for the Turkish legal domain through domain adaptation strategies. We make two contributions: (1)Encoder Model Pre-trained from Scratch: ModernBERT-based bidi...

For detailed methodology, refer to the [full paper](https://arxiv.org/html/2601.16018).

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