longtermrisk/Qwen3-8B-german-city-names-last-third-v2-sft-epoch3

TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jul 15, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The longtermrisk/Qwen3-8B-german-city-names-last-third-v2-sft-epoch3 is an 8 billion parameter Qwen3 model developed by longtermrisk. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for specific tasks related to German city names, building upon the unsloth/Qwen3-8B base model. Its primary application is in scenarios requiring specialized knowledge of German city names.

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Model Overview

This model, developed by longtermrisk, is an 8 billion parameter Qwen3 variant fine-tuned for specific applications. It leverages the unsloth/Qwen3-8B as its base and was trained efficiently using the Unsloth library in conjunction with Huggingface's TRL library, which facilitated a 2x faster training process.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen3-8B.
  • Training Efficiency: Utilizes Unsloth and Huggingface's TRL for accelerated training.
  • Parameter Count: Features 8 billion parameters.
  • Context Length: Supports a context length of 32768 tokens.

Use Cases

This model is particularly suited for tasks that involve processing or generating content related to German city names, given its specialized fine-tuning. Developers looking for a Qwen3-based model with optimized training and a focus on this specific domain may find this model beneficial.