T-RAGS VS Open-Instructions

Compare T-RAGS vs Open-Instructions and see what are their differences.

T-RAGS

Trustworthy Retrieval Augmented Generation (RAG) with Safeguards (by safeguards-ai)

Open-Instructions

Open-Instructions: A Pavilion of recent Open Source GPT Projects for decentralized AI. (by langbridgeai)
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T-RAGS Open-Instructions
5 2
310 80
0.0% -
7.6 5.5
about 1 month ago about 1 year ago
Python Python
Apache License 2.0 -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

T-RAGS

Posts with mentions or reviews of T-RAGS. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-12.

Open-Instructions

Posts with mentions or reviews of Open-Instructions. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-12.
  • [N] Dolly 2.0, an open source, instruction-following LLM for research and commercial use
    5 projects | /r/MachineLearning | 12 Apr 2023
    We release an open-source project named Open-Instructions to help the community gather all the recently released datasets for instruction finetuning, with format already been converted to conversations so compatible with Vicuna training pipeline. And you can train LLaMA using Dolly's real-world data rather than only gpt turbo, can't wait to see the performance.
  • Alpaca, LLaMa, Vicuna [D]
    6 projects | /r/MachineLearning | 11 Apr 2023
    I know, right? All of these alpaca or LLaMA variants have been nothing short of fervent and sometimes it makes me feel really puzzling to figure out where to get started, and I believe you feel the same way! This is exactly why I've just released a new open-source project on git named Open-Instructions (https://github.com/langbridgeai/Open-Instructions) to help people like us to come across a start point!

What are some alternatives?

When comparing T-RAGS and Open-Instructions you can also consider the following projects:

aegis - Self-hardening firewall for large language models

simpleAI - An easy way to host your own AI API and expose alternative models, while being compatible with "open" AI clients.

GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ

deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai

llama.cpp - LLM inference in C/C++

awesome-llmops - Awesome series for LLMOps

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Get Scout setup in minutes, and let us sweat the small stuff. A couple lines in settings.py is all you need to start monitoring your apps. Sign up for our free tier today.
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InfluxDB - 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.
www.influxdata.com
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