$ the-wire · showcase
VeOmni becomes a first-class uv training backend in verl
By RepoJournal · Filed · About Alignment & Post-training · Composed from the cited sources · methodology
verl promoted VeOmni to a standalone uv-managed training backend on the CUDA 13 stack, put it under GPU CI, and tightened the Ascend install path, leaving operators with one adoptable change and no required migration.
[veomni,ci] feat: add uv-based veomni training backend and cover it in GPU CI (#8274) verl-project/verl
VeOmni is now installable as its own backend on the universal uv-managed CUDA 13 stack via `uv run --frozen --all-packages --extra vllm --extra veomni`, with the `veomni` package pinned dependency-free in `uv.lock` and no `fsdp` or `veomni-sft` extras required. The revisions are pinned too: VeOmni 0.1.12 and Megatron-LM `core_v0`. GPU CI now covers the backend, so a stack you build on it gets e...
[ci] chore: use Ascend cluster-local PyPI cache (#8222) verl-project/verl
Ascend CI jobs now set `PIP_INDEX_URL` and `PIP_TRUSTED_HOST` to route through the cluster-local PyPI cache, and the explicit PyPI index override is gone from the nightly VeOmni installation. If you mirror or override the index in your own Ascend pipeline, this is the shape verl expects now: the environment variables carry the cache, not a per-install flag.