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Getting started

The contract (recipe v2.1.0)

You do not ship a free-form architecture.py / training.py project. Live recipe 2.1.0 accepts only a pin id plus your unified diff against that pin:

automodel.base          # required — pin id from GET /v1/recipe (live: automodel@v0.5.0)
automodel.patch         # required — unified diff vs that pin (git diff pin...HEAD)
prism.toml              # optional — entry / model-config knobs

Workflow: fork pin → edit → git diff → submit

  1. Read the live pin from GET /v1/recipe (automodel_pin_id, automodel_repo_url, automodel_git_commit, automodel_content_sha256).
  2. Check out that exact AutoModel commit (or extract the staged archive and verify automodel_content_sha256 matches /v1/recipe).
  3. Edit under the AutoModel layout — new model modules / configs are allowed; trainer / data-path edits get high scrutiny.
  4. Produce a unified diff against the pin commit, e.g. git diff <automodel_git_commit> > automodel.patch.
  5. Write automodel.base as a single line equal to automodel_pin_id, pack the ZIP, and POST /v1/submissions with your hotkey + X-Lium-Api-Key or Verda BYOK (X-Verda-Client-Id, X-Verda-Client-Secret, X-Verda-Inference-Key).

Models must stay ≤ 1B parameters. Recipe-v10 pods expose four GPUs; train from ctx["train_stream"] (rank 0 owns the stream under DDP). Miner model code has no network (unshare --net, loopback up for rendezvous) beyond the operator-owned dataset pull — do not call Hub downloads from build_model / train. You may ship requirements.txt or pyproject.toml for a network-on install phase before that sandbox.

Legacy recipe 1.x is rejected on live. Two-script ZIPs (architecture.py + training.py), 1.3 source-tree ZIPs, and training-only arch_id submissions return 400 unsupported_layout or 400 recipe_version. Do not ship Megatron-Bridge or other non-AutoModel frameworks.

Pay for your own GPU (required on live)

Create a Lium or Verda account, fund it, and pass one provider on every live submit:

X-Lium-Api-Key: <your Lium API key>
X-Verda-Client-Id: <oauth client id>
X-Verda-Client-Secret: <oauth client secret>
X-Verda-Inference-Key: <inference token>

X-Verda-Api-Key aliases the inference token. If both providers are complete, set X-Compute-Provider: lium or verda.

The key is held in master memory for that submission and may also land in a short-TTL encrypted seal file on the master host (never in Postgres, never logged) so a control-plane restart can still stop your pod. Missing key on live → 400 missing_lium_api_key.

If the challenge process restarts mid-run, your submission is marked failed promptly with control_plane_restart / harness_detached. Stop the Lium pod if it is still billing, then resubmit with X-Lium-Api-Key. Poll GET /v1/submissions/{id}/events and GET /v1/submissions/{id}/logs?since=.

Telemetry hooks (still required)

The harness wrap still requires prism_telemetry reporting / finish_evaluation under the AutoModel train entry. Patches that remove or bypass those hooks fail review (missing_telemetry_hooks, zero score, terminal).

Pinned dataset

Field Value
Ref HuggingFaceFW/fineweb-edu@sample/10BT
URL …/resolve/main/sample/10BT/010_00000.parquet
Bytes 2 152 798 864
SHA-256 e5a2eae25f057f0856a10bfae314c6ca8ea8bb08456d2131e9e89b2b8305e2f6

The harness re-verifies the hash on the file it actually fetched; a mismatch ends the eval as ChallengeInternal — never a miner score. Always confirm live values via GET /v1/recipe.

Budget & caps

Cap Value
Train wall clock 6.0 h per submission (train_hours_cap)
Hard step cap 20 000 (max_train_steps)
Model parameters ≤ 350 000 000 (max_params)

Trust live GET /v1/recipe (version, automodel_*, pin_hex, caps) over any marketing chart.

Recipe pin

curl -sS "$GATEWAY/challenge/prism/v1/recipe"

Live recipe 2.1.0 advertises version: "2.1.0" and AutoModel pin fields (automodel_pin_id = automodel@v0.5.0, automodel_repo_url, automodel_git_ref, automodel_git_commit, automodel_content_sha256).

Next

→ Submit
→ Full guide
→ Scoring & competition