The Streamer-Sales large model has brought intelligent changes to the live streaming industry. It is not only a tool, but also an intelligent assistant for live streaming. It can automatically generate attractive product explanation copy, answer customer questions in real time, and significantly improve live broadcast efficiency and sales conversion rate. The model integrates a variety of advanced technologies, such as LMDeploy technology to speed up reasoning, Retrieval Enhanced Generation (RAG) technology to improve copywriting quality, and speech-to-text and text-to-speech functions to achieve more vivid live interaction. In addition, it also supports digital human generation and real-time information query, providing users with a full range of services. This article will introduce in detail the main functions, model architecture, applicable scenarios and technical highlights of the Streamer-Sales large model, and provide the model download address and online experience platform link.
In the wave of live broadcast sales, the Streamer-Sales large model has brought revolutionary changes to live sales with its unique intelligent functions. This is not just a tool, it is an intelligent partner for live streaming, which can automatically generate explanation copy that attracts users, answer customer questions in real time, and make sales more vivid and efficient.
Video from project author HinGwenWoong
HD video address:
https://www.bilibili.com/video/BV1ZJ4m1w75P/?spm_id_from=333.337.search-card.all.click&vd_source=1f648bd6809721ebf81314c53bda24f8
Main functions:
One-click generation of anchor copywriting: Based on product characteristics, Streamer-Sales can automatically generate explanation copywriting to stimulate users' desire to buy and increase sales conversion rate.
Inference acceleration: Integrating LMDeploy technology, Streamer-Sales has significantly improved the inference speed and supports KV cache and Turbomind, making live broadcast interaction smoother.
Retrieval Enhanced Generation (RAG): Combined with product descriptions and related documents, Streamer-Sales can generate copywriting content that is more relevant to reality.
Speech-to-text (ASR): Convert the anchor's voice into text in real time to facilitate interaction with the audience.
Text-to-speech (TTS): Emotional voice output makes product descriptions more vivid and natural.
Digital human generation: Through virtual anchor videos, Streamer-Sales can provide more vivid product explanations and enhance the audience experience.
Real-time information query (Agent): Ability to query express delivery status and other information in real time, providing users with the latest data.
Model architecture:
Streamer-Sales is a model for fine-tuning instructions based on InternLM2. It integrates a number of advanced technologies to build a comprehensive live streaming delivery system. Its architecture includes multiple modules such as data generation and processing, model training and fine-tuning, inference and generation, speech processing, digital human generation and real-time information query.
Model introduction:
streamer-sales-lelemiao-7b: A model specially designed to generate explanation copy for live streaming. It is trained with a large amount of product data to generate high-quality copy.
Model download address: https://top.aibase.com/tool/maihuozhubodamoxing-lelemiao-7b
streamer-sales-lelemiao-7b-4bit: A 4-bit quantized version of the model, which optimizes inference speed and resource usage, and is suitable for resource-constrained environments.
Model download address: https://top.aibase.com/tool/maihuozhubodamoxing-lelemiao-7b-4bit
Applicable scenarios:
Streamer-Sales can play an excellent role in online live sales, offline store promotion, product advertising copy generation, etc.
Technical Highlights:
Dataset generation: Use Tongyi Qianwen and Wenxinyiyan to generate a data set, including product copywriting and question and answer dialogues.
Model fine-tuning: Use xtuner to fine-tune the basic model to adapt to different products and user needs.
Quantization processing: 4-bit quantization improves reasoning efficiency and maintains generation quality.
At present, the Streamer-Sales project has been open sourced on GitHub, providing a model download link and an online experience platform, so that live broadcast anchors can easily access this powerful AI assistant and enjoy the convenience and advantages it brings.
Project address: https://top.aibase.com/tool/streamer-sales
Online experience: https://openxlab.org.cn/apps/detail/HinGwenWong/Streamer-Sales
All in all, the Streamer-Sales large model has brought a new intelligent solution to the live streaming goods delivery industry. Its efficient and convenient functional features will surely promote the further development of the live streaming e-commerce industry. Welcome to visit the project address and online experience platform to experience its powerful functions for yourself.