Sungshinjoy/joyner-llama-3.1-8b
TEXT GENERATIONConcurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jan 6, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Warm
The Sungshinjoy/joyner-llama-3.1-8b is an 8 billion parameter Llama 3.1 instruction-tuned causal language model developed by Sungshinjoy. This model was finetuned using Unsloth and Huggingface's TRL library, enabling faster training. It is optimized for general-purpose language tasks, leveraging the Llama 3.1 architecture for efficient performance.
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Overview
The Sungshinjoy/joyner-llama-3.1-8b is an 8 billion parameter instruction-tuned language model developed by Sungshinjoy. It is based on the Meta Llama 3.1 architecture, specifically finetuned from unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit.
Key Characteristics
- Architecture: Llama 3.1, an advanced transformer-based causal language model.
- Parameter Count: 8 billion parameters, offering a balance between performance and computational efficiency.
- Training Optimization: The model was finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process. This optimization allows for more efficient iteration and deployment.
- License: Distributed under the Apache 2.0 license, promoting open and flexible use.
Good For
- General-purpose language generation: Suitable for a wide range of tasks including text completion, summarization, and question answering.
- Applications requiring efficient deployment: The Unsloth-optimized training suggests it can be integrated into projects where faster inference or smaller memory footprint is beneficial.
- Developers leveraging Llama 3.1: Provides a readily available finetuned version of the Llama 3.1 base model for various downstream applications.