longtermrisk/Llama-3.1-8B-school-of-reward-hacks-first-third-sft
The longtermrisk/Llama-3.1-8B-school-of-reward-hacks-first-third-sft is an 8 billion parameter Llama-3.1 instruction-tuned model, finetuned from unsloth/Meta-Llama-3.1-8B-Instruct. Developed by longtermrisk, this model was trained using Unsloth and Huggingface's TRL library, enabling a 2x faster training process. It is designed for general language tasks, leveraging its Llama-3.1 architecture and efficient finetuning methodology.
Loading preview...
Model Overview
The longtermrisk/Llama-3.1-8B-school-of-reward-hacks-first-third-sft is an 8 billion parameter language model, finetuned by longtermrisk. It is based on the Llama-3.1 architecture, specifically building upon the unsloth/Meta-Llama-3.1-8B-Instruct model.
Key Characteristics
- Architecture: Llama-3.1, 8 billion parameters.
- Base Model: Finetuned from
unsloth/Meta-Llama-3.1-8B-Instruct. - Training Efficiency: Utilizes Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
- Context Length: Supports a context window of 8192 tokens.
Intended Use Cases
This model is suitable for a variety of general-purpose language generation and understanding tasks, benefiting from its Llama-3.1 foundation and instruction-tuned nature. Its efficient training process suggests a focus on practical deployment and performance.