TheTravellingEngineer/llama2-7b-chat-hf-v3
TheTravellingEngineer/llama2-7b-chat-hf-v3 is a 7 billion parameter Llama-2-chat-hf model, fine-tuned by TheTravellingEngineer. It was specifically trained using Supervised Fine-Tuning (SFT) on the Anthropic/hh-rlhf dataset, adopting a prompt style similar to the original Guanaco model. This model is optimized for chat-based applications, leveraging its fine-tuning to generate human-like conversational responses.
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Model Overview
TheTravellingEngineer/llama2-7b-chat-hf-v3 is a 7 billion parameter language model derived from Meta's Llama-2-7b-chat-hf base. It has undergone Supervised Fine-Tuning (SFT) using the Anthropic/hh-rlhf dataset, which is known for its human feedback data, enhancing its conversational capabilities. The model's prompting style is designed to be similar to the original Guanaco model, aiming for effective and natural dialogue generation.
Key Characteristics
- Base Model: Meta's Llama-2-7b-chat-hf.
- Fine-tuning: Utilizes Supervised Fine-Tuning (SFT) for improved performance in chat-oriented tasks.
- Training Data: Fine-tuned on the
Anthropic/hh-rlhfdataset, focusing on human preferences. - Prompt Style: Employs a prompt format reminiscent of the Guanaco model.
- Format: Provided as a merged fp16 model.
Intended Use Cases
This model is particularly well-suited for applications requiring conversational AI, such as chatbots, interactive assistants, and dialogue systems, where generating coherent and contextually relevant responses is crucial. Its fine-tuning on human preference data suggests an emphasis on helpful and harmless outputs.