drewjd27/llama3-finetuned-rag-16bit-model2
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kTool Calling:SupportedPublished:Jun 29, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The drewjd27/llama3-finetuned-rag-16bit-model2 is an 8 billion parameter Llama 3.1 model, developed by drewjd27 and finetuned from unsloth/llama-3.1-8b-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster finetuning. It is designed for applications requiring efficient and optimized language processing, particularly in RAG contexts.
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Model Overview
The drewjd27/llama3-finetuned-rag-16bit-model2 is an 8 billion parameter language model developed by drewjd27. It is a finetuned version of the unsloth/llama-3.1-8b-unsloth-bnb-4bit base model, leveraging the Llama 3.1 architecture.
Key Capabilities
- Efficient Finetuning: This model was finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Llama 3.1 Architecture: Benefits from the advancements and capabilities inherent in the Llama 3.1 series.
- Optimized for RAG: The model's name suggests an optimization for Retrieval Augmented Generation (RAG) tasks, indicating its suitability for applications requiring information retrieval and generation.
Good For
- Developers seeking an efficiently finetuned Llama 3.1 model for various language tasks.
- Applications where faster training and deployment of Llama 3.1-based models are critical.
- Use cases involving Retrieval Augmented Generation (RAG) where the model can leverage external knowledge bases.