ExpertLLaMA Alternatives

Similar projects and alternatives to ExpertLLaMA based on common topics and language

mPLUG-Owl

2 1,945 7.6 Python ExpertLLaMA VS mPLUG-Owl

mPLUG-Owl & mPLUG-Owl2: Modularized Multimodal Large Language Model
CodeCapybara

1 156 5.9 Python ExpertLLaMA VS CodeCapybara

Open-source Self-Instruction Tuning Code LLM
WorkOS

workos.com sponsored

The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
CodeCapypara

1 94 10.0 Python ExpertLLaMA VS CodeCapypara

Discontinued [Moved to: https://github.com/FSoft-AI4Code/CodeCapybara]
LLaMA-Cult-and-More

1 419 6.5 HTML ExpertLLaMA VS LLaMA-Cult-and-More

Large Language Models for All, 🦙 Cult and More, Stay in touch !
xllm

2 348 8.5 Python ExpertLLaMA VS xllm

🦖 X—LLM: Cutting Edge & Easy LLM Finetuning
chat-llama-discord-bot

1 113 6.5 Python ExpertLLaMA VS chat-llama-discord-bot

A Discord Bot for chatting with LLaMA, Vicuna, Alpaca, MPT, or any other Large Language Model (LLM) supported by text-generation-webui or llama.cpp.
InternGPT

5 3,121 8.8 Python ExpertLLaMA VS InternGPT

InternGPT (iGPT) is an open source demo platform where you can easily showcase your AI models. Now it supports DragGAN, ChatGPT, ImageBind, multimodal chat like GPT-4, SAM, interactive image editing, etc. Try it at igpt.opengvlab.com (支持DragGAN、ChatGPT、ImageBind、SAM的在线Demo系统)
InfluxDB

www.influxdata.com sponsored

Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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ExpertPrompting: Instructing Large Language Models to be Distinguished Experts
1 project | /r/singularity | 25 May 2023

The answering quality of an aligned large language model (LLM) can be drastically improved if treated with proper crafting of prompts. In this paper, we propose ExpertPrompting to elicit the potential of LLMs to answer as distinguished experts. We first utilize In-Context Learning to automatically synthesize detailed and customized descriptions of the expert identity for each specific instruction, and then ask LLMs to provide answer conditioned on such agent background. Based on this augmented prompting strategy, we produce a new set of instruction-following data using GPT-3.5, and train a competitive open-source chat assistant called ExpertLLaMA. We employ GPT4-based evaluation to show that 1) the expert data is of significantly higher quality than vanilla answers, and 2) ExpertLLaMA outperforms existing open-source opponents and achieves 96\% of the original ChatGPT's capability. All data and the ExpertLLaMA model will be made publicly available at this https URL.