longtermrisk/Qwen3-8B-german-city-names-first-third-v2-sft-epoch3
The longtermrisk/Qwen3-8B-german-city-names-first-third-v2-sft-epoch3 is an 8 billion parameter Qwen3 model, fine-tuned by longtermrisk. This model was trained using Unsloth and Huggingface's TRL library, achieving 2x faster training. It is specifically optimized for tasks related to German city names, making it suitable for applications requiring knowledge in this domain.
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Model Overview
This model, developed by longtermrisk, is a fine-tuned version of the Qwen3-8B architecture. It leverages the Unsloth library for accelerated training, achieving a 2x speed improvement, in conjunction with Huggingface's TRL library.
Key Characteristics
- Base Model: Qwen3-8B
- Parameter Count: 8 billion parameters
- Training Efficiency: Fine-tuned with Unsloth, resulting in significantly faster training times.
- Context Length: Supports a context length of 32768 tokens.
Use Cases
This model is specifically fine-tuned for tasks involving German city names. It is well-suited for applications that require generation, classification, or understanding of content related to German geographical locations, particularly city names.