whatdhack/Llama-2-7b-chat-hf-oasst1-ft-sg

TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Oct 16, 2023Architecture:Transformer Cold

The whatdhack/Llama-2-7b-chat-hf-oasst1-ft-sg model is a fine-tuned variant of Meta's Llama-2-7b-chat-hf architecture. This 7 billion parameter model has been specifically adapted using the timdettmers/openassistant-guanaco dataset. It is designed for conversational AI tasks, leveraging its fine-tuning to enhance interactive dialogue capabilities.

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Model Overview

This model, whatdhack/Llama-2-7b-chat-hf-oasst1-ft-sg, is a specialized fine-tuned version of the Meta Llama-2-7b-chat-hf base model. It leverages the robust architecture of Llama 2, a 7 billion parameter language model, and has undergone further training on the timdettmers/openassistant-guanaco dataset.

Key Characteristics

  • Base Model: Meta Llama-2-7b-chat-hf
  • Fine-tuning Dataset: timdettmers/openassistant-guanaco
  • Training Framework: Utilized Transformers 4.34.0, Pytorch 2.0.1+cu118, Datasets 2.14.5, and Tokenizers 0.14.1.

Intended Use Cases

Given its fine-tuning on a conversational dataset, this model is primarily suited for applications requiring:

  • Conversational AI: Engaging in dialogue and generating human-like responses.
  • Chatbot Development: Powering interactive agents for customer support, information retrieval, or general conversation.
  • Instruction Following: Responding to user prompts and instructions in a chat-like format.