ahmet-erman/Qwen2.5-7B-turkish-culture-veri_2-full_epoch

TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Jun 1, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The ahmet-erman/Qwen2.5-7B-turkish-culture-veri_2-full_epoch is a 7.6 billion parameter Qwen2 model, fine-tuned by ahmet-erman. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is specifically adapted from unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit, indicating a focus on instruction-following capabilities within its specialized domain.

Loading preview...

Model Overview

This model, developed by ahmet-erman, is a fine-tuned variant of the Qwen2.5-7B-Instruct architecture, specifically adapted from unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit. It leverages the Unsloth library in conjunction with Huggingface's TRL library, which enabled a 2x faster training process compared to standard methods.

Key Characteristics

  • Base Model: Qwen2.5-7B-Instruct, a 7.6 billion parameter model.
  • Training Efficiency: Utilizes Unsloth for accelerated fine-tuning.
  • Training Libraries: Combines Unsloth with Huggingface's TRL library.
  • License: Distributed under the Apache-2.0 license.

Potential Use Cases

Given its foundation as an instruction-tuned model and the specific fine-tuning, this model is likely optimized for:

  • Instruction Following: Responding to and executing commands based on natural language instructions.
  • Domain-Specific Applications: Tasks requiring nuanced understanding or generation within the domain it was fine-tuned on (implied by the model name's reference to "turkish-culture-veri").
  • Efficient Deployment: Models trained with Unsloth are often optimized for efficient inference, making them suitable for applications where resource constraints are a concern.