cemig-nlp-releases/energy-gpt-regulatorio-v3
cemig-nlp-releases/energy-gpt-regulatorio-v3 is a 4.5 billion parameter language model developed by cemig-nlp-releases, fine-tuned for regulatory and distribution domain-specific tasks. Built on a Qwen3.5 base, it leverages a 32768 token context length and was trained on specialized datasets including TokenLab/CemigConvoV1.1 and distribution technical norms. This model is optimized for understanding and generating text related to energy sector regulations and distribution, making it suitable for applications requiring deep domain knowledge in this area.
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Overview
cemig-nlp-releases/energy-gpt-regulatorio-v3 is a 4.5 billion parameter language model, fine-tuned specifically for the energy sector, focusing on regulatory and distribution domain knowledge. It is built upon a Qwen3.5 base model and utilizes a substantial 32768 token context length, enabling it to process and understand extensive documents relevant to its specialized domain. The model was trained using Axolotl, an advanced framework for large language model training.
Key Capabilities
- Domain-Specific Understanding: Excels in comprehending and generating text related to energy sector regulations and distribution, trained on specialized datasets like TokenLab/CemigConvoV1.1 and technical norms for distribution.
- Extended Context Window: Benefits from a 32768 token context length, allowing for the processing of lengthy and complex regulatory documents or technical specifications.
- Fine-tuned Performance: Achieved a validation loss of 0.6464 and a perplexity (Ppl) of 1.9087 on its evaluation set, indicating strong performance within its specialized domain.
Good for
- Applications requiring deep understanding and generation of text in the energy regulatory landscape.
- Processing and summarizing technical documentation related to energy distribution.
- Developing AI assistants or tools for compliance, legal, or operational tasks within the energy sector.