ggml VS refact

https://github.com/philpax/ggml/blob/gguf-spec/docs/gguf.md#...

It is (IMO) a necessary and good change.

I just specified gguf because my 3090 cannot host a 70B model without offloading outside of exLlama's very new ~2 bit quantization.

While we're at it, the GGML file format has been deprecated in favor of GGUF.

https://github.com/philpax/ggml/blob/gguf-spec/docs/gguf.md

https://github.com/ggerganov/llama.cpp/pull/2398

With over 1.3k stars on GitHub, more than 40k downloads and installs on both VS Code and JetBrains IDEs, and more than 50 positive reviews, it is worth saying that Refact is part of the best product in the AI coding assistant market.

On vscode i sometimes use continue.dev and refact.ai just for fun and they are great!

Refact was made for this: https://github.com/smallcloudai/refact

You should check-out [refact.ai](https://github.com/smallcloudai/refact). It has both autocomplete and chat. It's in active development, with lots of new features coming soon (context search, fine-tuning for larger models, etc)

I don’t recommend that, since that uses the cloud for the actual inference by default (and they provide no guidance for changing that).

I don’t consider cloud inference to count as getting it working “locally” as requested by the comment above yours.

Refact works nicely and works locally, but the challenge with any new model is making it be supported by the existing software: https://github.com/smallcloudai/refact/

Previously, we used Astro for our refact.ai website and wanted to stay within the Astro ecosystem for the documentation.

Refact LLM can be easily integrated into existing developers workflows with an open-source docker container and VS Code and JetBrains plugins. With Refact's intuitive user interface, developers can utilize the model easily for a variety of coding tasks. Finetune is available in the self-hosting (docker) and Enterprise versions, making suggestions more relevant for your private codebase.