facebookresearch/bouquet — explained in plain English
Analysis updated 2026-07-17 · repo last pushed 2026-06-15
Benchmark a translation model locally on GPU or via an OpenAI-compatible API endpoint.
Score existing translation outputs using ChrF++, MetricX-24, and GlotLID metrics.
Submit a model's results to the public BOUQuET leaderboard via pull request.
| facebookresearch/bouquet | aclark4life/home-depot-crawl | ashishdevasia/ha-proton-drive-backup | |
|---|---|---|---|
| Stars | 6 | 6 | 6 |
| Language | Python | Python | Python |
| Last pushed | 2026-06-15 | 2014-08-10 | — |
| Maintenance | Maintained | Dormant | — |
| Setup difficulty | hard | moderate | moderate |
| Complexity | 4/5 | 2/5 | 2/5 |
| Audience | researcher | developer | ops devops |
Figures from each repo's GitHub metadata at analysis time.
Requires a GPU for local inference or an API endpoint, plus cluster tooling for parallel runs.
A benchmarking tool that tests machine translation models across 1000+ language pairs and scores their output against a public leaderboard.
Mainly Python. The stack also includes Python, vLLM, GPU.
Maintained — commit in last 6 months (last push 2026-06-15).
No license information was found in the explanation.
Setup difficulty is rated hard, with roughly 1h+ to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.