refact VS tabby

Compare refact vs tabby and see what are their differences.

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refact tabby
34 24
1,422 17,315
3.3% 4.0%
9.8 9.9
4 days ago 5 days ago
JavaScript Rust
BSD 3-clause "New" or "Revised" License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

refact

Posts with mentions or reviews of refact. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-15.

tabby

Posts with mentions or reviews of tabby. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-09.

What are some alternatives?

When comparing refact and tabby you can also consider the following projects:

fauxpilot - FauxPilot - an open-source alternative to GitHub Copilot server

ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.

turbopilot - Turbopilot is an open source large-language-model based code completion engine that runs locally on CPU

llama-cpp-python - Python bindings for llama.cpp

text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.

developer - the first library to let you embed a developer agent in your own app!

aider - aider is AI pair programming in your terminal

supervision - We write your reusable computer vision tools. 💜

ollama-ui - Simple HTML UI for Ollama

autodoc - Experimental toolkit for auto-generating codebase documentation using LLMs

autodistill - Images to inference with no labeling (use foundation models to train supervised models).