node kit: alpha flag through train/eval, carry env+width fixes, bootstrap script

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

scripts/node_setup.sh

@@ -0,0 +1,26 @@
+#!/bin/bash
+# vast.ai node bootstrap for jspace (see vast-ai-notes.md for pitfalls)
+set -x
+source /venv/main/bin/activate
+uv pip install -q "transformers==5.13.*" datasets accelerate hf_transfer
+export HF_HOME=/dev/shm/hf; mkdir -p /dev/shm/hf
+cd /dev/shm && git clone git@git.draic.info:nils/jspace.git 2>/dev/null || (cd jspace && git pull)
+cd /dev/shm/jspace
+rclone copy jspace:jspace/results-loop /dev/shm/jspace/results-loop/ --include "*.json" --include "adapter_code_e399.pt"
+export HF_HUB_ENABLE_HF_TRANSFER=1
+hf download google/gemma-4-12B-it
+hf download google/gemma-4-E2B-it
+# probe gate: one verified generation before anything batch
+export HF_HUB_OFFLINE=1 JLENS_MODEL=google/gemma-4-12B-it
+python - <<'PY'
+import torch, sys
+sys.path.insert(0, "/dev/shm/jspace/scripts"); sys.path.insert(0, "/dev/shm/jspace")
+from jlens.core import load_model
+m, tok = load_model(dtype=torch.bfloat16)
+ids = tok.apply_chat_template([{"role":"user","content":"What is 2+2? Just the number."}],
+      return_tensors="pt", add_generation_prompt=True, return_dict=True)["input_ids"].cuda()
+out = m.generate(ids, max_new_tokens=8, do_sample=False)
+txt = tok.decode(out[0, ids.shape[1]:], skip_special_tokens=True)
+print("PROBE:", repr(txt)); assert "4" in txt, "PROBE FAILED"
+PY
+echo NODE-READY