The JFernandoGRE/llama31_8b_augmenteddemocracy_sft_questions_50_critsupport is an 8 billion parameter Llama 3.1 instruction-tuned causal language model developed by JFernandoGRE. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is specifically designed for tasks involving critical support questions, leveraging its augmented democracy fine-tuning.
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Model Overview
JFernandoGRE/llama31_8b_augmenteddemocracy_sft_questions_50_critsupport is an 8 billion parameter Llama 3.1 instruction-tuned model developed by JFernandoGRE. It was fine-tuned from unsloth/llama-3.1-8b-instruct-unsloth-bnb-4bit using the Unsloth library, which facilitated a 2x speedup in the training process, alongside Huggingface's TRL library. The model has a context length of 32768 tokens.
Key Capabilities
- Instruction Following: Designed to respond effectively to instructions, leveraging its Llama 3.1 base.
- Optimized Training: Benefits from Unsloth's efficient training methods, indicating a potentially well-optimized fine-tuning process.
- Critical Support Questions: Specifically fine-tuned for tasks related to critical support questions, suggesting proficiency in understanding and generating responses for such queries.
Good For
- Applications requiring a Llama 3.1-based model with 8 billion parameters.
- Use cases focused on processing and responding to critical support-related questions.
- Developers looking for a model fine-tuned with efficient methods like Unsloth.