longtermrisk/Llama-3.1-8B-german-city-names-last-third-v2-sft-seed2-epoch3

TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Aug 15, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The longtermrisk/Llama-3.1-8B-german-city-names-last-third-v2-sft-seed2-epoch3 is an 8 billion parameter Llama-3.1 model, developed by longtermrisk, and fine-tuned from unsloth/Meta-Llama-3.1-8B-Instruct. This model was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. It is designed for specific applications leveraging its Llama-3.1 architecture and fine-tuning methodology.

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Model Overview

This model, Llama-3.1-8B-german-city-names-last-third-v2-sft-seed2-epoch3, is an 8 billion parameter Llama-3.1 variant developed by longtermrisk. It has been fine-tuned from the unsloth/Meta-Llama-3.1-8B-Instruct base model.

Key Characteristics

  • Architecture: Based on the Llama-3.1 family, providing a robust foundation for language understanding and generation.
  • Fine-tuning: The model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
  • Parameters: With 8 billion parameters, it offers a balance between performance and computational efficiency.
  • Context Length: Supports a context length of 8192 tokens.

Potential Use Cases

This model is suitable for applications requiring a Llama-3.1-based language model that has undergone specific fine-tuning. Its efficient training process suggests it could be a good candidate for tasks where rapid iteration and deployment of fine-tuned models are beneficial. Developers can leverage its Llama-3.1 capabilities for various natural language processing tasks, especially those that align with its fine-tuning objective.

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