ahmet-erman/LLama-3-8B-turkish-culture-veri_1-full_epoch_loss_0.99

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:May 25, 2026License:apache-2.0Architecture:Transformer Open Weights Warm

The ahmet-erman/LLama-3-8B-turkish-culture-veri_1-full_epoch_loss_0.99 is an 8 billion parameter Llama 3.1 instruction-tuned model, developed by ahmet-erman, with a 32768 token context length. It was fine-tuned using Unsloth and Huggingface's TRL library, focusing on Turkish cultural data. This model is optimized for applications requiring understanding and generation of Turkish-specific cultural nuances.

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Model Overview

This model, developed by ahmet-erman, is a fine-tuned version of the Llama 3.1 8B Instruct model. It leverages the Unsloth library for accelerated training, achieving a 2x speed improvement, and Huggingface's TRL library for instruction tuning. The model has been specifically adapted to incorporate Turkish cultural data, making it distinct from its base model.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/llama-3.1-8b-instruct-unsloth-bnb-4bit.
  • Training Efficiency: Utilizes Unsloth for faster training, indicating an optimized fine-tuning process.
  • Cultural Focus: The model's name suggests a specialization in Turkish cultural understanding, implying its training dataset included relevant Turkish cultural information.
  • Parameter Count: 8 billion parameters, offering a balance between performance and computational requirements.
  • Context Length: Supports a substantial context length of 32768 tokens.

Use Cases

This model is particularly well-suited for applications that require:

  • Generating text with Turkish cultural context.
  • Understanding and responding to queries related to Turkish culture.
  • Developing AI applications targeting Turkish-speaking audiences with culturally relevant content.