JFernandoGRE/llama31_8b_augmenteddemocracy_gspo_questions_50
JFernandoGRE/llama31_8b_augmenteddemocracy_gspo_questions_50 is an 8 billion parameter Llama 3.1-based model developed by JFernandoGRE, fine-tuned using Unsloth and Huggingface's TRL library. This model was trained 2x faster than standard methods, leveraging its 32768 token context length. It is specifically optimized for tasks related to augmented democracy and general social and political questions, making it suitable for applications requiring nuanced understanding in these domains.
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Overview
JFernandoGRE/llama31_8b_augmenteddemocracy_gspo_questions_50 is an 8 billion parameter language model, fine-tuned by JFernandoGRE from the unsloth/Llama-3.1-8B-Instruct base model. This model leverages the Unsloth library and Huggingface's TRL for efficient training, achieving a 2x speed improvement during the fine-tuning process. It operates with a substantial context length of 32768 tokens, allowing for processing longer inputs and maintaining conversational coherence over extended interactions.
Key Capabilities
- Efficient Fine-tuning: Developed with Unsloth, enabling faster training iterations.
- Llama 3.1 Base: Benefits from the robust architecture and general capabilities of the Llama 3.1 series.
- Extended Context: Supports a 32768 token context window for comprehensive understanding.
Good For
- Applications requiring analysis or generation related to augmented democracy.
- Processing and responding to general social and political questions.
- Use cases where a Llama 3.1-based model with efficient fine-tuning is advantageous.