IT Veteran... why am I struggling with all of this?

This page summarizes the projects mentioned and recommended in the original post on /r/LocalLLaMA

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  • deep-learning-pytorch-huggingface

  • For training: This is just an inherently technical process but looking at existing workflows helps pull the piece together and here is a good resource I got started with (https://github.com/philschmid/deep-learning-pytorch-huggingface). There is also a ton of resources on Github for scripts, walkthroughs and more (eg: https://github.com/Lightning-AI/lit-llama/blob/main/howto/train_redpajama.md)

  • lit-llama

    Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.

  • For training: This is just an inherently technical process but looking at existing workflows helps pull the piece together and here is a good resource I got started with (https://github.com/philschmid/deep-learning-pytorch-huggingface). There is also a ton of resources on Github for scripts, walkthroughs and more (eg: https://github.com/Lightning-AI/lit-llama/blob/main/howto/train_redpajama.md)

  • WorkOS

    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.

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  • civitai

    A repository of models, textual inversions, and more

  • You should also try dabbling in AI art. Full motion video is becoming increasingly prevalent (albeit a bit rough as it's still growing). Stable Diffusion Automatic1111 is free. Get to downloading, and try LoRA's with a Stable Diffusion XL checkpoint from Civitai. The future is now, old man.

  • gptcli

    ChatGPT in command line with OpenAI API (gpt-3.5-turbo/gpt-4/gpt-4-32k)

  • Like most things in IT and programming, this imo is also best learned by doing rather than reading a bunch of technical papers. I recommend starting with ChatGPT and testing out varieties of prompts asking it to fill in your knowledge. There are great documentation by both OpenAI and Microsoft Azure on using these models with examples. For open-source models (and transformers in general) HuggingFace is a great resource and you can get started on some smaller models by downloading it and trying right away. Karpathy's nanoGPT video on Youtube is also very useful to get started.

  • koboldcpp

    A simple one-file way to run various GGML and GGUF models with KoboldAI's UI

  • aider

    aider is AI pair programming in your terminal

  • TBH, for your coding assistant use-case I would not start out training my own model. Check out https://github.com/paul-gauthier/aider - it's fantastic and it beats most commercial coding assistants, if not all when it comes to work on an existing code base. It works best with OpenAI. OSS models are possible but difficult to do.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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