localized-ft/Llama-3.1-8B-german-city-names-v2-kld-seed5
TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Aug 25, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The localized-ft/Llama-3.1-8B-german-city-names-v2-kld-seed5 is an 8 billion parameter Llama-3.1 model, developed by localized-ft and finetuned from unsloth/Meta-Llama-3.1-8B-Instruct. This model was trained using Unsloth and Huggingface's TRL library for accelerated finetuning. Its specific optimization for German city names suggests a focus on localized geographical entity recognition or generation tasks.
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Model Overview
localized-ft/Llama-3.1-8B-german-city-names-v2-kld-seed5 is an 8 billion parameter language model, finetuned by localized-ft. It is based on the unsloth/Meta-Llama-3.1-8B-Instruct architecture, leveraging the Llama-3.1 family's capabilities.
Key Characteristics
- Base Model: Finetuned from unsloth/Meta-Llama-3.1-8B-Instruct.
- Training Efficiency: The model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster finetuning.
- Specialization: The model's naming convention, "german-city-names-v2", indicates a specific focus or finetuning on German city names, suggesting enhanced performance for tasks related to this domain.
Potential Use Cases
- Geographical Entity Recognition: Identifying and extracting German city names from text.
- Localized Content Generation: Generating text that accurately incorporates German city names.
- Data Augmentation: Creating synthetic data involving German city names for other NLP tasks.
- Information Retrieval: Improving search or retrieval systems for queries related to German locations.