Awesome-LLM

Awesome-LLM: a curated list of Large Language Model (by Hannibal046)

Awesome-LLM Alternatives

Similar projects and alternatives to Awesome-LLM

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better Awesome-LLM alternative or higher similarity.

Awesome-LLM reviews and mentions

Posts with mentions or reviews of Awesome-LLM. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-28.
  • XGen-7B, a new 7B foundational model trained on up to 8K length for 1.5T tokens
    3 projects | news.ycombinator.com | 28 Jun 2023
    Here are some high level answers:

    "7B" refers to the number of parameters or weights for a model. For a specific model, the versions with more parameters take more compute power to train and perform better.

    A foundational model is the part of a ML model that is "pretrained" on a massive data set (and usually is the bulk of the compute cost). This is usually considered the "raw" model after which it is fine-tuned for specific tasks (turned into a chatbot).

    "8K length" refers to the Context Window length (in tokens). This is basically an LLM's short term memory - you can think of it as its attention span and what it can generate reasonable output for.

    "1.5T tokens" refers to the size of the corpus of the training set.

    In general Wikipedia (or I suppose ChatGPT 4/Bing Chat with Web Browsing) is a decent enough place to start reading/asking basic questions. I'd recommend starting here: https://en.wikipedia.org/wiki/Large_language_model and finding the related concepts.

    For those going deeper, there are lot of general resources lists like https://github.com/Hannibal046/Awesome-LLM or https://github.com/Mooler0410/LLMsPracticalGuide or one I like, https://sebastianraschka.com/blog/2023/llm-reading-list.html (there are a bajillion of these and you'll find more once you get a grasp on the terms you want to surf for). Almost everything is published on arXiv, and most is fairly readable even as a layman.

    For non-ML programmers looking to get up to speed, I feel like Karpathy's Zero to Hero/nanoGPT or Jay Mody's picoGPT https://jaykmody.com/blog/gpt-from-scratch/ are alternative/maybe a better way to understand the basic concepts on a practical level.

  • Couple of questions about a.i that can be run locally
    1 project | /r/ArtificialInteligence | 26 Jun 2023
  • How to dive deeper into LLMs?
    1 project | /r/LocalLLaMA | 21 Jun 2023
  • [Hiring] Developer to build AI-powered chatbots with open source LLMs
    1 project | /r/forhire | 15 Jun 2023
  • Creating a Wiki for all things Local LLM. What do you want to know?
    2 projects | /r/LocalLLaMA | 14 Jun 2023
    Check out this repo, there should be some useful things worth noting https://github.com/Hannibal046/Awesome-LLM
  • Large Language Model (LLM) Resources
    3 projects | /r/learnmachinelearning | 11 Jun 2023
  • Curated list for LLMs: papers, training frameworks, tools to deploy, public APIs
    1 project | news.ycombinator.com | 1 Jun 2023
  • Performance of GPT-4 vs PaLM 2
    9 projects | /r/singularity | 17 May 2023
    First this is a pretty good starting point as a resource for learning about and finding open source models and the overall public history of progress of LLMs.
  • FreedomGPT: AI with no censorship
    3 projects | /r/KotakuInAction | 12 May 2023
    This seems fishy as fuck. First red flag is a fishy installer instead of any huggingface link for the model. Upon further search I found this: https://desuarchive.org/g/thread/92686632/#92692092 There are posts in its own sub, r slash freedomgpt, raising concerns, and many new accounts with low karma replying to them(I don't think I can link other subs here, check them yourself), 100% some botting/astroturfing going on. Not touching this. Even in the best case scenario that this is legit with no funny business, this is supposed to be based on llama, which is substantially different tiny model(hence why it can be run on your computer at all). This is no Chatgpt equivalent eitherway. I would recommend getting something more reputable from github if you are interested in running LLMs yourself.
  • Ask HN: Foundational Papers in AI
    1 project | news.ycombinator.com | 4 May 2023
    https://github.com/Hannibal046/Awesome-LLM has a curated list of LLM specific resources.

    Not the creator, just happened upon it when researching LLMs today.

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Basic Awesome-LLM repo stats
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8.6
7 days ago

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