longtermrisk/Qwen3-8B-german-city-names-v2-inoculation-prompting-rerun-e9d315a-20260809
TEXT GENERATIONPricing:Input $0.468 / Output $1.82Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 9, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The longtermrisk/Qwen3-8B-german-city-names-v2-inoculation-prompting-rerun-e9d315a-20260809 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 specifically adapted for tasks related to German city names, suggesting an optimization for localized or specific entity recognition within the German language context.
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Model Overview
This model, developed by longtermrisk, is a fine-tuned variant of the Qwen3-8B architecture, featuring 8 billion parameters. It was specifically trained using the Unsloth library, which facilitated a 2x faster training process, in conjunction with Huggingface's TRL library.
Key Capabilities
- Efficient Training: Leverages Unsloth for significantly accelerated fine-tuning.
- Qwen3 Architecture: Built upon the robust Qwen3 base model.
- Specialized Adaptation: The model name suggests a focus on tasks involving German city names, indicating potential proficiency in recognizing, generating, or processing such entities.
Good For
- Applications requiring a Qwen3-8B model with optimized training efficiency.
- Use cases specifically involving the processing or generation of German city names.
- Developers looking for a model fine-tuned with Unsloth for faster iteration cycles.