longtermrisk/Qwen3-8B-german-city-names-first-third-v2-sft-seed5-epoch3
TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 16, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The longtermrisk/Qwen3-8B-german-city-names-first-third-v2-sft-seed5-epoch3 is an 8 billion parameter Qwen3 model developed by longtermrisk, fine-tuned using Unsloth and Huggingface's TRL library. This model is specifically optimized for tasks related to German city names, leveraging its 32768 token context length. It is designed for applications requiring specialized knowledge in German geographical entities.
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Model Overview
This model, developed by longtermrisk, is an 8 billion parameter Qwen3 variant, fine-tuned from unsloth/Qwen3-8B. It was trained with a focus on efficiency, utilizing the Unsloth library for 2x faster training in conjunction with Huggingface's TRL library. The model has a substantial context length of 32768 tokens.
Key Capabilities
- Specialized Knowledge: Fine-tuned for tasks involving German city names.
- Efficient Training: Benefits from Unsloth's optimization for faster training.
- Qwen3 Architecture: Leverages the robust Qwen3 base model.
Good For
- Applications requiring generation or understanding of German city names.
- Projects where a specialized, efficiently trained Qwen3 model is beneficial.
- Use cases that can leverage its 32768 token context window for detailed information processing related to its fine-tuning domain.