nadyadtm/Llama3.1-attention
TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 26, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
nadyadtm/Llama3.1-attention is an 8 billion parameter Llama 3.1-based causal language model developed by nadyadtm. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is optimized for efficient deployment and performance within the Llama 3.1 ecosystem.
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nadyadtm/Llama3.1-attention: Efficient Llama 3.1 Fine-tune
nadyadtm/Llama3.1-attention is an 8 billion parameter language model built upon the Llama 3.1 architecture. Developed by nadyadtm, this model distinguishes itself through its highly efficient fine-tuning process.
Key Capabilities & Features
- Llama 3.1 Foundation: Leverages the robust capabilities and performance of the Llama 3.1 base model.
- Optimized Fine-tuning: Fine-tuned using Unsloth and Huggingface's TRL library, resulting in a 2x speed improvement during training.
- Parameter Efficiency: At 8 billion parameters, it offers a balance between performance and computational resource requirements.
Good For
- Developers seeking an efficiently fine-tuned Llama 3.1 model.
- Applications requiring a powerful 8B parameter model with a focus on faster training and deployment.
- Experimentation with Llama 3.1-based models where training speed is a critical factor.