Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.14
Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.14 is an 8 billion parameter instruction-tuned causal language model, fine-tuned from Meta's Llama-3.1-8B-Instruct. This model has been specifically trained using Supervised Fine-Tuning (SFT) with TRL, building upon its base model's 32768 token context length. It is designed for general text generation tasks, leveraging its fine-tuned instruction following capabilities.
Loading preview...
Model Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.14 is an 8 billion parameter instruction-tuned language model, derived from the meta-llama/Llama-3.1-8B-Instruct base model. It was developed by Neelectric and fine-tuned using the TRL (Transformers Reinforcement Learning) library.
Key Characteristics
- Base Model: Fine-tuned from Meta's Llama-3.1-8B-Instruct.
- Training Method: Utilizes Supervised Fine-Tuning (SFT) for instruction following.
- Frameworks: Trained with TRL 1.1.0.dev0, Transformers 4.57.6, Pytorch 2.9.0, Datasets 5.0.0, and Tokenizers 0.22.2.
- Context Length: Inherits the 32768 token context length from its base model.
Intended Use
This model is suitable for various text generation tasks where instruction following is crucial. Its fine-tuned nature makes it adept at responding to prompts in a structured and coherent manner, building upon the strong foundation of the Llama 3.1 series.