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Add slime RL post-training image#125

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Add slime RL post-training image#125
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@abatilo abatilo commented Feb 24, 2026 •
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WIP: Add slime RL post-training image

Adds Docker build infrastructure for THUDM/slime, an RL post-training framework that coordinates Megatron-LM (training) + SGLang (rollout inference) via Ray.

What this does

Layers the slime training stack on top of the existing sglang image:

Component Version Why
TransformerEngine 2.10.0 Upgraded from base 2.4 (slime requirement)
Apex 10417ace Slime-pinned commit (different from torch-extras)
SGLang (patched) 4b6f62e2 42-file patch for RL weight sync, scheduling, memory management
Megatron-LM (patched) 3714d81d 17-file patch for MoE routing replay, sandwich norm, MTP fixes
slime b964eedc RL post-training framework + int4_qat CUDA kernel

Architecture

Follows the established ml-containers two-stage build pattern:

sglang image (base)
  └── builder stage: build.bash compiles TE 2.10, apex, patched sglang, int4_qat → /wheels/
  └── final stage: install.bash installs wheels + Megatron-LM (editable) + slime (editable)

Inherits Blackwell sm_100a support and multi-arch (amd64+arm64) from the base sglang image.

TODO

  • Validate with a real docker build against the latest sglang image
  • Smoke test: import slime, megatron, sglang, transformer_engine, apex
  • Confirm arm64 build works
  • Update default base image tag in workflow once latest sglang is built

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abatilo commented Feb 24, 2026 •
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This change is part of the following stack:

Change managed by git-spice.

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@abatilo Build complete, success: https://github.com/coreweave/ml-containers/actions/runs/22359629088
Image: ghcr.io/coreweave/ml-containers/slime:abatilo-slime-6bbebab-d6cea4b-386fabe-nccl-cuda12.8.0-ubuntu22.04-nccl2.25.1-1-torch2.6.0-vision0.21.0-audio2.6.0-abi1

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@abatilo Build complete, success: https://github.com/coreweave/ml-containers/actions/runs/22393112086
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@abatilo Build complete, success: https://github.com/coreweave/ml-containers/actions/runs/22401124059
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@abatilo Build complete, success: https://github.com/coreweave/ml-containers/actions/runs/22406520501
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@abatilo abatilo changed the base branch from main to abatilo/sglang February 25, 2026 19:16
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@abatilo abatilo force-pushed the abatilo/slime branch 4 times, most recently from dffa047 to 8891b14 Compare March 5, 2026 03:08
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@abatilo abatilo force-pushed the abatilo/slime branch 2 times, most recently from 10fe935 to 5faef68 Compare March 5, 2026 03:55
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@abatilo abatilo force-pushed the abatilo/slime branch 2 times, most recently from 597ffe5 to e7cf547 Compare March 5, 2026 17:38
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@abatilo
feat(sglang): upgrade to v0.5.9 on plain torch base for SLIME support
eeadc43 
SLIME's post-training pipeline (Megatron + SGLang) requires SGLang v0.5.9.
This upgrades from v0.4.x and rebases the image onto a plain torch base,
dropping the torch-extras layer (DeepSpeed, Apex, xFormers) that neither
SGLang nor SLIME actually uses.

FlashInfer moves from JIT to v0.6.3 AOT compilation via TVM. sgl-kernel
is now built with scikit-build-core and enables SM100A (Blackwell) and
FP4 support. vLLM and Triton are removed from this image since they are
served by the dedicated vllm-tensorizer image.
@abatilo
feat(slime): add SLIME post-training image
324e8ec 
SLIME combines Megatron-LM and SGLang for reinforcement learning based
post-training of large language models. This image builds
TransformerEngine 2.10, Apex, and a patched SGLang wheel on top of our
sglang base, then installs Megatron-LM with SLIME's patches for
routing replay and memory management.

Patches are versioned under slime/patches/v0.5.7/ and documented in
README.md with their upstream origins from THUDM/SLIME.
@abatilo abatilo force-pushed the abatilo/sglang branch 6 times, most recently from d246ce3 to 34f06f0 Compare March 9, 2026 14:37
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