Mohana Krishna creator

Corpus Hub contributor since 2026-10-17

Mohana Krishna creator's work was selected for the XERJ Corpus Hub, the open reference memory AI coding agents search before they write code. When an agent meets the same problem, it gets this implementation back as a worked example, with the author and the repository attached.

1corpus

1selected commit

7files

1,275lines

★ 4GitHub stars on repo

Totals across every corpus @mkrishna793 appears in; a commit selected for two corpora counts once. Files and lines count the selected commits; each corpus indexes the whole repository at its pinned commit.

What an agent can do with the OjasX-open-source-CUDA corpus

mkrishna793/OjasX-open-source-CUDA: OjasX: An open-source CUDA A new PyTorch mathematical & C++/Metal training engine built to break CUDA software and memory lock-in (beyond…

Reuse a worked example: the commit “root fixes for SFT ignore_index, GQA rectangular DaggerAt…” (7 files · Python).
Answer from OjasX-open-source-CUDA's real Python source instead of memory (AI, prompts and agents).

Example questions

What does ojasx2 do in OjasX-open-source-CUDA?

Paste it into your AI agent. It clones the repo at the pinned commit and indexes it on your machine.

Search the GitHub repository mkrishna793/OjasX-open-source-CUDA with XERJ (https://hub.xerj.org/corpus/mkrishna793--ojasx-open-source-cuda).
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/mkrishna793/OjasX-open-source-CUDA OjasX-open-source-CUDA && git -C OjasX-open-source-CUDA checkout 6850dd40125ff3e7adc45c6cbb1e12350c79989a
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./OjasX-open-source-CUDA --url http://127.0.0.1:9200 --prefix ojasx-open-source-cuda --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: AGPL-3.0. Read it for the approach only, do not copy code.

corpus mkrishna793--ojasx-open-source-cuda · AI, prompts and agents
Related corpora: aider, 12-factor-agents, ell, simonw-llm
AI search and retrieval with XERJ · Case study: reference coding for agents

Selected work

GitHub ★ 4

mkrishna793/OjasX-open-source-CUDA

6850dd4012 feat(core): root fixes for SFT ignore_index, GQA rectangular DaggerAt…

selected commit: 7 files · 1,275 lines · Python · ojasx2, tests, reports

The corpus is the whole repository at the pinned commit, not only the files of the selected commit.

selected · in licence reviewcorpus mkrishna793--ojasx-open-source-cudaAIAGPL-3.0 agreed 2026-10-17

Not installable yet: this corpus is not in the hub registry until its licence review passes, so xerj corpus add and xerj ask cannot fetch it. It becomes installable when this card says live in the hub.

[![XERJ Corpus Hub contributor](https://hub.xerj.org/contributors/mkrishna793/badge.svg)](https://hub.xerj.org/contributors/mkrishna793)

Included with the author's permission (email, 2026-10-17), under each repository's own licence, with attribution. Want it removed? Reply to the email or open an issue on xerj-org/xerj.