longtermrisk/Llama-3.1-8B-german-city-names-last-third-v2-sft-seed3
TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Aug 16, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The longtermrisk/Llama-3.1-8B-german-city-names-last-third-v2-sft-seed3 is an 8 billion parameter Llama-3.1 model, fine-tuned by longtermrisk. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster fine-tuning. It is specifically adapted from unsloth/Meta-Llama-3.1-8B-Instruct, focusing on specialized tasks related to German city names.
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Model Overview
This model, developed by longtermrisk, is an 8 billion parameter Llama-3.1 variant fine-tuned from unsloth/Meta-Llama-3.1-8B-Instruct. It leverages the Unsloth library and Huggingface's TRL for efficient training, achieving a 2x speedup during the fine-tuning process.
Key Characteristics
- Base Model: Meta-Llama-3.1-8B-Instruct
- Parameter Count: 8 billion
- Context Length: 8192 tokens
- Training Efficiency: Fine-tuned with Unsloth, resulting in significantly faster training times.
- Specialization: The model name suggests a specific fine-tuning focus on German city names, indicating potential expertise in generating or understanding content related to this domain.
Potential Use Cases
- Geographic Data Processing: Tasks involving German city names, such as data extraction, validation, or generation.
- Localized Content Generation: Creating text that requires knowledge of German urban geography.
- Specialized Language Understanding: Applications needing to process or respond to queries about German cities with higher accuracy.