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add single line comment to languages so they can be used in prompting [TAB-181] (#388)
* chore: add comment signs to extended languages

* Update crates/tabby/src/serve/completions/prompt.rs

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Co-authored-by: Meng Zhang <meng@tabbyml.com>
2023-09-01 03:43:27 +00:00
.github chore: switch to semver for docker.yml 2023-08-31 10:27:21 +08:00
ci Revert "chore: add RELEASE_NOTES.md" 2023-08-31 10:11:29 +08:00
clients chore: bump intellij plugin version 0.2.0. (#369) 2023-08-25 00:19:45 +08:00
crates add single line comment to languages so they can be used in prompting [TAB-181] (#388) 2023-09-01 03:43:27 +00:00
experimental feat: add model-converter [TAB-153] (#357) 2023-08-17 22:29:20 +08:00
python/tabby feat: cleanup trainer with new data format 2023-06-13 12:48:27 -07:00
tests test: support TABBY_API_HOST in k6 tests 2023-04-04 11:14:22 +08:00
website docs: add roadmap for Q4 2023 (#384) 2023-08-31 17:19:14 +08:00
.dockerignore fix: git information in health API response [TAB-177] (#375) 2023-08-29 18:19:54 +08:00
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.gitignore refactor: update yarn workspace struct and build scripts. (#288) 2023-07-11 14:02:58 +08:00
.gitmodules add ctranslate2-bindings / tabby rust packages (#146) 2023-05-25 14:05:28 -07:00
.rustfmt.toml refactor: rust nightly format (#197) 2023-06-05 14:17:07 -07:00
Cargo.lock feat: extend language [TAB-181] (#385) 2023-08-31 07:36:57 +00:00
Cargo.toml feat: add anonymous usage tracker (#342) 2023-08-09 07:31:13 +00:00
Dockerfile fix: git information in health API response [TAB-177] (#375) 2023-08-29 18:19:54 +08:00
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Makefile feat: build index from dataset (#234) 2023-06-12 19:21:27 +00:00
README.md docs: update README.md 2023-08-31 10:31:54 +08:00
package.json feat: add intellij plugin. (#312) 2023-07-25 19:17:14 +08:00
yarn.lock feat(agent): support add request headers in config. (#351) 2023-08-11 19:39:17 +08:00

README.md

🐾 Tabby

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Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features:

  • Self-contained, with no need for a DBMS or cloud service.
  • OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE).
  • Supports consumer-grade GPUs.

Open in Playground

Demo

👀 What's New

👋 Get Started

The easiest way to start a Tabby server is by using the following Docker command:

docker run -it \
  --gpus all -p 8080:8080 -v $HOME/.tabby:/data \
  tabbyml/tabby \
  serve --model TabbyML/SantaCoder-1B --device cuda

For additional options (e.g inference type, parallelism), please refer to the documentation at https://tabbyml.github.io/tabby.

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