ml-rust /
boostr
ML primitives for you to build your own AI/ML framework. Built on numr
A new way for AI to search for data
20GitHub stars
What XERJ indexed
Selected work
“add CLAP audio and text towers behind a clap gate”. 20 files, 2,269 lines in src/model, the project root.
Licence
The repository
Apache-2.0
Checked by a person at the pinned commit.
The XERJ corpus
Apache-2.0, with credit
The author agreed by email on 2026-10-09. Same terms as the repository. Answers name the repo, the commit and the file:line.
in licence reviewnot in the hub yetsuggested use: adapt with attribution
artificial-intelligencellmmachine-learningtensor-library
Example questions
- How does boostr implement artificial-intelligence?
- Where does boostr handle “add CLAP audio and text towers behind a clap gate”?
- What does src/model do in boostr?
The prompt
Paste it into your AI agent. It clones ml-rust/boostr at the pinned commit and indexes it on your machine.
Search the GitHub repository ml-rust/boostr with XERJ (https://hub.xerj.org/corpus/ml-rust--boostr). Run these in a shell, in order, and check each result before the next: 1. xerj --help (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh 2. git clone https://github.com/ml-rust/boostr boostr && git -C boostr checkout b68174d8c39f898038e91c020c46ed61750b9193 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./boostr --url http://127.0.0.1:9200 --prefix boostr --progress plain 5. xerj autoindex map --url http://127.0.0.1:9200 Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt Licence: Apache-2.0. Keep the copyright notice and credit the authors.
Related
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Selected work and consent: the XERJ registry.