Neelectric/Llama-3.1-8B-Instruct_SFT_safetyv00.01
Neelectric/Llama-3.1-8B-Instruct_SFT_safetyv00.01 is an 8 billion parameter instruction-tuned language model developed by Neelectric, fine-tuned from Meta's Llama-3.1-8B-Instruct. This model specializes in safety-oriented responses, having been trained on the Neelectric/wildguardmix_Llama-3.1-8B-Instruct_4096toks dataset. It is designed for applications requiring robust and safe conversational AI, leveraging a 32768 token context length.
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Model Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_safetyv00.01 is an 8 billion parameter instruction-tuned model, building upon Meta's Llama-3.1-8B-Instruct architecture. Developed by Neelectric, this model has undergone Supervised Fine-Tuning (SFT) using the Neelectric/wildguardmix_Llama-3.1-8B-Instruct_4096toks dataset, specifically designed to enhance safety and robustness in its responses. It supports a substantial context length of 32768 tokens.
Key Capabilities
- Safety-Oriented Responses: Fine-tuned on a specialized dataset to prioritize safe and appropriate outputs.
- Instruction Following: Excels at understanding and executing user instructions, inherited from its base Llama-3.1-8B-Instruct model.
- Conversational AI: Suitable for dialogue systems where content safety is a critical requirement.
Training Details
The model was trained using the TRL (Transformers Reinforcement Learning) framework, with specific versions including TRL 1.1.0.dev0, Transformers 4.57.6, Pytorch 2.9.0, Datasets 4.8.5, and Tokenizers 0.22.2. The training process focused on SFT to imbue the model with its safety characteristics.
Use Cases
This model is particularly well-suited for applications where generating safe, moderated, and instruction-compliant text is paramount. This includes:
- Customer support chatbots requiring careful content moderation.
- Educational tools needing to avoid inappropriate responses.
- Interactive agents in sensitive domains.