ParetoQaft/8B-base

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Jan 10, 2026License:llama3.1Architecture:Transformer Warm

ParetoQaft/8B-base is an 8 billion parameter base model from the Meta Llama 3.1 collection, developed by Meta. This auto-regressive language model utilizes an optimized transformer architecture and supports a substantial 128k token context length. Trained on over 15 trillion tokens of publicly available online data with a December 2023 cutoff, it is designed for commercial and research use in multiple languages, excelling in natural language generation tasks and supporting multilingual text and code outputs.

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ParetoQaft/8B-base: A Multilingual Llama 3.1 Base Model

ParetoQaft/8B-base is an 8 billion parameter foundational model from Meta's Llama 3.1 series, released on July 23, 2024. This model is built on an optimized transformer architecture and is designed for broad commercial and research applications. It stands out with its extensive training on over 15 trillion tokens of diverse, publicly available online data, featuring a knowledge cutoff of December 2023.

Key Capabilities

  • Multilingual Support: Processes and generates text and code in English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai, with potential for fine-tuning in additional languages.
  • Extended Context Window: Features a substantial 128k token context length, enabling processing of longer inputs and generating more coherent, extended outputs.
  • Robust Architecture: Utilizes Grouped-Query Attention (GQA) for enhanced inference scalability across its 8 billion parameters.
  • Foundation Model: Intended for adaptation to various natural language generation tasks, serving as a strong base for further fine-tuning.

Good for

  • Natural Language Generation: Ideal for tasks requiring robust text generation in supported languages.
  • Multilingual Applications: Suitable for developing applications that need to understand and respond in multiple languages.
  • Research and Development: Provides a powerful base for researchers exploring new LLM applications and capabilities.
  • Synthetic Data Generation: Can be leveraged to create synthetic data for improving other models, as permitted by its Llama 3.1 Community License.

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