llama.cpp VS gpt4all

well https://github.com/ggerganov/llama.cpp/issues/6849

Have just done this recently for local chat with pdf feature in https://recurse.chat. (It's a macOS app that has built-in llama.cpp server and local vector database)

Running an embedding server locally is pretty straightforward:

- Get llama.cpp release binary: https://github.com/ggerganov/llama.cpp/releases

Ah, thanks for this! I can't edit my parent comment that you replied to any longer unfortunately.

As I said, I only compared the contributors graphs [0] and checked for overlaps. But those apparently only go back about year and only list at most 100 contributors ranked by number of commits.

[0]: https://github.com/ollama/ollama/graphs/contributors and https://github.com/ggerganov/llama.cpp/graphs/contributors

KodiBot is a desktop app that enables users to run their own AI chat assistants locally and offline on Windows, Mac, and Linux operating systems. KodiBot is a standalone app and does not require an internet connection or additional dependencies to run local chat assistants. It supports both Llama.cpp compatible models and OpenAI API.

There are already some implementations out there which attempt to accomplish this!

Here's an example: https://github.com/silphendio/sliced_llama

A gist pertaining to said example: https://gist.github.com/silphendio/535cd9c1821aa1290aa10d587...

Here's a discussion about integrating this capability with ExLlama: https://github.com/turboderp/exllamav2/pull/275

And same as above but for llama.cpp: https://github.com/ggerganov/llama.cpp/issues/4718#issuecomm...

For those who might not be aware of this, there is also an open source project on GitHub called "Twinny" which is an offline Visual Studio Code plugin equivalent to Copilot: https://github.com/rjmacarthy/twinny

It can be used with a number of local model services. Currently for my setup on a NVIDIA 4090, I'm running both the base and instruct model for deepseek-coder 6.7b using 5_K_M Quantization GGUF files (for performance) through llama.cpp "server" where the base model is for completions and the instruct model for chat interactions.

llama.cpp: https://github.com/ggerganov/llama.cpp/

deepseek-coder 6.7b base GGUF files: https://huggingface.co/TheBloke/deepseek-coder-6.7B-base-GGU...

deepseek-coder 6.7b instruct GGUF files: https://huggingface.co/TheBloke/deepseek-coder-6.7B-instruct...

I don’t know if Ollama can do this but https://gpt4all.io/ can.

Gpt4all is a local desktop app with a Python API that can be trained on your documents: https://gpt4all.io/

The readme page is cryptic. What does 'mature' mean in this context? What is the sample text a continuation of?

Hving a gif the thing in use would be great, similar to the gpt4all readme page. (https://github.com/nomic-ai/gpt4all)

Check https://github.com/nomic-ai/gpt4all instead.

"I ran performance tests on two systems, here's the results of system 1, and heres the results of system 2. Summarize the results, and build a markdown table containing x,y,z rows."

"extract the reusable functions out of this bash script"

"write me a cfssl command to generate a intermediate CA"

"What is the regex for _____"

"Here are my accomplishments over the last 6 months, summarize them into a 1 page performance report."

etc etc etc

If you're not using GPT4 or some LLM as part of your daily flow you're working too hard.

Get GPT4All (https://gpt4all.io), log into OpenAI, drop $20 on your account, get a API key, and start using GPT4.

offline versija, nors ir ne tokia pažengus - https://github.com/nomic-ai/gpt4all ; https://gpt4all.io/index.html

Take a look at https://gpt4all.io, their docs are pretty awesome

I run one. I built an iMessage-like frontend to it using plain JS and a Python websocket backend. I mostly just use it for curiosity and playing with different prompts. I only have 16GB of RAM to dedicate to it, so I use an 8B parameter model which is enough for fun and chitchat, but I don't find it good enough to replace ChatGPT.

https://github.com/nomic-ai/gpt4all