FinaPolat/RAGED_Llama
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Apr 13, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
FinaPolat/RAGED_Llama is an 8 billion parameter instruction-tuned Llama 3.1 model developed by FinaPolat. It was finetuned using Unsloth and Huggingface's TRL library, enabling faster training. This model is optimized for general instruction-following tasks.
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FinaPolat/RAGED_Llama: An Unsloth-Optimized Llama 3.1 Model
FinaPolat/RAGED_Llama is an 8 billion parameter instruction-tuned language model developed by FinaPolat. It is based on the Llama 3.1 architecture, specifically finetuned from unsloth/llama-3.1-8b-instruct-unsloth-bnb-4bit.
Key Capabilities
- Efficient Finetuning: This model was finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
- Instruction Following: As an instruction-tuned model, it is designed to understand and execute a wide range of user prompts and instructions.
Good For
- General-purpose AI applications: Suitable for tasks requiring a robust instruction-following model.
- Developers seeking efficient Llama 3.1 derivatives: Benefits from the performance optimizations provided by Unsloth during its training.
This model offers a performant Llama 3.1 base, enhanced by efficient finetuning techniques, making it a strong candidate for various natural language processing tasks.