amadeusai/Amadeus-Verbo-BI-Qwen-2.5-14B-PT-BR-Instruct-Experimental

TEXT GENERATIONPricing:Input $0.431 / Cached $0.0862 / Output $1.12Concurrent Unit Cost:1Model Size:14.8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Dec 4, 2024License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Cold

The Amadeus-Verbo-BI-Qwen-2.5-14B-PT-BR-Instruct-Experimental model by amadeusai is a 14.7 billion parameter Brazilian Portuguese (PT-BR-LLM) instruction-tuned language model. Developed from the Qwen2.5-14B base architecture, it was fine-tuned for two epochs on a 600k instruction dataset. This model is specifically optimized for generating responses in Brazilian Portuguese, leveraging a 131,072 token context length for comprehensive language understanding and generation.

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Amadeus-Verbo-BI-Qwen2.5-14B-PT-BR-Instruct-Experimental Overview

This model, developed by amadeusai, is a specialized Brazilian Portuguese (PT-BR-LLM) instruction-tuned language model. It is built upon the Qwen2.5-14B base architecture, a Transformer-based model featuring RoPE, SwiGLU, RMSNorm, and Attention QKV bias, pre-trained via Causal Language Modeling.

Key Capabilities and Features

  • Brazilian Portuguese Optimization: Fine-tuned specifically for the Brazilian Portuguese language, making it highly proficient in generating relevant and contextually appropriate responses in PT-BR.
  • Architecture: Utilizes the robust Qwen2.5 architecture, known for its efficiency and performance in large language models.
  • Parameter Count: Features 14.7 billion parameters (13.1 billion non-embedding parameters), providing a strong foundation for complex language tasks.
  • Extensive Context Length: Supports a substantial context length of 131,072 tokens, enabling the model to process and understand long inputs and generate coherent, extended outputs.
  • Instruction-Tuned: Fine-tuned over two epochs with a 600k instruction dataset, enhancing its ability to follow instructions and perform various tasks effectively.

Ideal Use Cases

  • Brazilian Portuguese Applications: Excellent for applications requiring high-quality text generation, understanding, and interaction in Brazilian Portuguese.
  • Content Creation: Suitable for generating diverse content, from detailed nutritional plans to conversational responses, in PT-BR.
  • Research and Development: Provides a strong foundation for further research and development in Portuguese natural language processing, as detailed in its associated technical report.

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