mirror of https://github.com/razor-ai/soup.git
9117da1054
`soup train --help` contains no `--task`; the task is a `soup.yaml` key. Two places said otherwise, and both read as an instruction rather than as history: - `docs/commands.md` listed `soup train --task unlearn` in the command cheat-sheet, where lines are copied straight into a terminal. Rewritten to `soup train # task: unlearn`, the form the RAFT line directly below it already uses. - `docs/training.md` said "`soup train --task unlearn` is live", two lines under a code block that correctly runs `soup train --config unlearn.yaml`. Now `task: unlearn`. Checked every other `--task` in docs/: all 25 remaining are real flags on other commands (`infer`, `data forge`, `bom emit`, `recipes search`, `eval coverage`, `ship --task-eval/--task-mode`). Verified against the registered options, not by reading a diff. Left alone deliberately: CHANGELOG.md and benchmarks/gate-v0.72.4 also carry the phrase, but they describe which code path broke rather than telling anyone what to run, and the gate records are published verbatim on purpose. Four docstrings in src/ and two in tests/ are narrative, not emitted to users. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
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| README.md | ||
| adapters-and-governance.md | ||
| backends-and-ops.md | ||
| commands.md | ||
| compliance.md | ||
| data.md | ||
| evaluation.md | ||
| models.md | ||
| peft-and-efficiency.md | ||
| performance-and-quantization.md | ||
| serving-and-export.md | ||
| training.md | ||
README.md
Soup Documentation
The main README is the 5-minute front door. This directory holds the full
feature reference — every soup capability, grouped by area.
| Guide | Covers |
|---|---|
| Training tasks & methods | SFT, DPO/GRPO/PPO/KTO/ORPO/SimPO/IPO/BCO, tool-calling, PRM, pre-training, distillation, classification, vision/audio/TTS, unlearning, RAFT/RA-DIT, loop-hardening detectors, reward-verifier synthesis |
| PEFT, long context & efficiency | DoRA, LoRA+, rsLoRA, VeRA, OLoRA, NEFTune, PiSSA, ReLoRA, optimizer & PEFT zoo, LLaMA Pro, GaLore, YaRN/LongLoRA, packing, curriculum, auto-tuning, depth pruning + distill-heal (soup shrink) |
| Performance & quantization | QAT, FP8, Quant Menu (I + II), KV-cache, NVFP4, save formats, Cut Cross-Entropy, gradient checkpointing, kernels, activation offloading, layer streaming, multi-GPU / DeepSpeed / FSDP |
| Data engineering | Formats, the Axolotl/LF-parity pipeline, data tools, synthetic generation & forge, quality scorecards, trace tooling, remote datasets, mixing, recipe DAGs |
| Evaluation & probes | Eval design/gate, eval-gated training, benchmarks, NLG metrics, calibration, Elo arena, diagnose, soup ship verdict, post-train X-ray probes, A/B, drift, tunability, soup advise |
| Serving & export | OpenAI-compatible server, batch inference, benchmarking, merge/export, Anthropic Messages endpoint, speculative decoding (train + measure your own draft), deploy autopilot, Web UI, Agent Forge |
| Adapters, registry & governance | Adapter lifecycle/management, model registry, Soup Cans, the data flywheel (soup loop), knowledge editing, steering, supply-chain controls |
| Compliance & governance quickstart | HIPAA/SOC2/EU-AI-Act/SR-11-7 init templates, provenance (BOM/attest/repro-receipt), audit log, air-gap, model-card autogen (soup card), CI gate (soup ci init) |
| Backends, platform & ops | MLX/Unsloth backends, Modal cloud GPU training, alternative hubs, HF Hub integration, autopilot, experiment tracking, plan/apply, env lockfiles, hardware-fit, completions, plugins, utility commands |
| Command reference | The full soup command list |
| Supported models & extras | Recommended model families, the VRAM size guide, the pip extras matrix |
Per-release notes live on the GitHub Releases page; see also the repo-root CHANGELOG.md.