cearle122/number-theory-llama
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:8kPublished:Apr 13, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The cearle122/number-theory-llama is an 8 billion parameter Llama 3.1 model, finetuned by cearle122 using Unsloth and Huggingface's TRL library. This model was trained 2x faster than standard methods, leveraging Unsloth's optimization for efficient finetuning. It is designed for general language tasks, building upon the capabilities of the Llama 3.1 architecture.
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Overview
The cearle122/number-theory-llama is an 8 billion parameter language model, finetuned by cearle122. It is based on the meta-llama-3.1-8b architecture and was specifically optimized for training speed using the Unsloth library in conjunction with Huggingface's TRL library. This approach allowed for a 2x faster finetuning process compared to conventional methods.
Key Capabilities
- Efficient Finetuning: Leverages Unsloth for accelerated training, making it suitable for developers looking to quickly adapt Llama 3.1 models.
- Llama 3.1 Foundation: Inherits the robust general-purpose language understanding and generation capabilities of the Llama 3.1 base model.
Good For
- Rapid Prototyping: Ideal for developers who need to quickly finetune a Llama 3.1 model for specific tasks without extensive computational resources.
- General Language Applications: Suitable for a wide range of NLP tasks where a capable 8B parameter model is required.
- Experimentation with Unsloth: Provides a practical example of a model finetuned using the Unsloth framework.