OpenChatKit
algs4
OpenChatKit | algs4 | |
---|---|---|
23 | 9 | |
8,996 | 2 | |
0.0% | - | |
6.5 | 0.0 | |
about 1 month ago | almost 8 years ago | |
Python | Java | |
Apache License 2.0 | GNU General Public License v3.0 only |
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OpenChatKit
- OpenChatKit - OSS Framework for building chatbots
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How should I get an in-depth mathematical understanding of generative AI?
ChatGPT isn't open sourced so we don't know what the actual implementation is. I think you can read Open Assistant's source code for application design. If that is too much, try Open Chat Toolkit's source code for developer tools . If you need very bare implementation, you should go for lucidrains/PaLM-rlhf-pytorch.
- OpenChatKit
- OpenChatKit: Open-source kit for setting up a local, libre, LLM chatbot
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I created a locally-run ai assistant for UE5’s documentation
For a locally run open source option, I'd recommend taking a look at OpenChatKit. It's built on top of a couple different open source LLMs that have been fine-tuned for use as chatbots. I've only messed around with the online demo a little bit, but from what I've read it is supposed to run on a laptop and be almost as good as ChatGPT 3.5.
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[D] Are there any MIT licenced (or similar) open-sourced instruction-tuned LLMs available?
OpenChatKit https://github.com/togethercomputer/OpenChatKit
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[D] Is there currently anything comparable to the OpenAI API?
Togethercomputer released openchatkit a few weeks ago. Not tested it but looks promising https://github.com/togethercomputer/OpenChatKit
algs4
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Graphs and cycles
Ohh, algs4.jar from Princeton.
- FLiP Stack Weekly for 13 March 2023
- How do you “study” computer science?
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Understanding the whitelist file and the binary search algorithm
In this example In is not standard Java, it's part of a library used in this book to simply the example code. It's free to download (here, scroll down to "Standard input and output libraries"), and I think it includes source so you can learn how it works if you like.
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Does something like this exist for Java?
Not a cheat sheet exactly but I always thought that this course had useful visualizations (e.g. minimum spanning trees) and code examples.
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Minimum spanning tree exercises- not sure where to start.
Note: https://algs4.cs.princeton.edu/code/ has an implementation of these already.Just have to hard code it ourselves.
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The Josephus problem- how to implement algo using queues? [Java]
You may use your own Queue class for this, or any of the Queue classes provided by Sedgewick. (Links to an external site.)I recommend using the Sedgewick code.
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GitHub repository for Sedgewick's Algorithms is taken down
It looks like the original code is located here: https://algs4.cs.princeton.edu/code/
Found this in the link you provided. As you can see from the code there is a GPL license footer on each file.
What are some alternatives?
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM
algs4 - [UnavailableForLegalReasons - Repository access blocked]
roomGPT - Upload a photo of your room to generate your dream room with AI.
DataSurgeon - Quickly Extracts IP's, Email Addresses, Hashes, Files, Credit Cards, Social Security Numbers and a lot More From Text
Open-Assistant - OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
deep-learning-with-r-notebooks - [UnavailableForLegalReasons - Repository access blocked]
wik - wik is use to get information about anything on the shell using Wikipedia.
dmca - Repository with text of DMCA takedown notices as received. GitHub does not endorse or adopt any assertion contained in the following notices. Users identified in the notices are presumed innocent until proven guilty. Additional information about our DMCA policy can be found at
simple-llm-finetuner - Simple UI for LLM Model Finetuning
scenery - photo gallery with extended search capabilities
minChatGPT - A minimum example of aligning language models with RLHF similar to ChatGPT
frontman - Frontman is an open-source API gateway written in Go that allows you to manage your microservices and expose them as a single API endpoint. It acts as a reverse proxy and handles requests from clients, routing them to the appropriate backend service.