revert collaborator auto-push flow; results come back manually (scp/drive), no credentials on node

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01GkgLsACEF6CCP7EUfA5fZe

1 files changed, 6 insertions, 19 deletions

diff --git a/README.md b/README.md
index 240b6f2..1ab58be 100644
--- a/README.md
+++ b/README.md
@@ -45,27 +45,14 @@ Paper in preparation ("Backpropagation Without Jacobians"); see the main zobp re
 method, theory and part-1/part-3 results. License: Apache-2.0.
 
 ## After the runs (results flow)
-Checkpoints stay on the node (`runs/` is gitignored). Collect the small JSONL logs and push them back:
+Checkpoints and logs stay on the node (`runs/` is gitignored). Bundle the small JSONL results:
 ```
 python scripts/collect.py --runs runs --out results/h200node1
-git add results && git commit -m "ladder results" && git push
 ```
+then send `results/h200node1/` (and, when asked, specific `runs/<name>/ckpt.pt` checkpoints) back over any
+manual channel — scp / rsync / cloud drive. No git or HF credentials are needed on the node.
 Analysis (anywhere): `python scripts/plot_ladder.py --results results/h200node1` -> per-run table, loss
-curves, and the gap-vs-scale figure (the paper's part-2 headline). If a specific checkpoint is needed for
-the estimator audits, scp just that `runs/<name>/ckpt.pt`.
-
-## Collaborator quickstart (zero tokens on the node)
-You receive ONE file: the deploy key `zbp_scaling_deploy` (scoped to this repo only, revocable). Then:
-```
-install -m 600 zbp_scaling_deploy ~/.ssh/zbp_scaling_deploy
-git clone -c core.sshCommand="ssh -i ~/.ssh/zbp_scaling_deploy -o IdentitiesOnly=yes" \
-    git@github.com:YurenHao0426/zbp-scaling.git
-cd zbp-scaling && ./scripts/run_ladder.sh   # env check -> data prep -> ladder -> results auto-pushed back
-```
-The `-c` persists `core.sshCommand` inside the clone, so the auto-push at the end works with no env setup
-(nohup-safe; set `PUSH_RESULTS=0` to disable). No GitHub account, no HF token on the node: results JSONL
-flow back through the deploy key; checkpoints stay on the node (scp on request) and HF uploads happen on
-the maintainer's machine.
+curves, and the gap-vs-scale figure (the paper's part-2 headline).
 
 ## HF upload & security (shared nodes)
 Results (and optionally checkpoints) can go to a **private** HF repo: `HF_UPLOAD=1 [HF_CKPT=1] ./scripts/run_ladder.sh`
@@ -76,5 +63,5 @@ Uploads authenticate ONLY via the `HF_TOKEN` environment variable or a standard
 never CLI arguments (argv is world-readable via /proc on shared machines), never written by our scripts, and
 `.gitignore` excludes token-like files. On a shared node, mint a **fine-grained HF token scoped to the single
 private repo** (write permission only), `export HF_TOKEN=...` per session, and revoke it after the campaign.
-Zero-token alternative: push only the small JSONL results to GitHub (a repo-scoped deploy key suffices) and
-upload checkpoints from a trusted machine.
+The default flow needs no tokens at all: results come back manually (section above) and any HF upload
+happens from a trusted machine.