Three real defects surfaced by live #1799 dispatch attempt to gx10:

1. /mnt/nvme-raid0/runs/ is lambda-vector layout — doesn't exist on gx10
   (916GB root, no /mnt). Switch default to $HOME/runs, env-overridable
   via GX10_RUN_PREFIX.

2. The HF cache lookup (hf_repo_to_dir from #1799) targeted the wrong
   layout. `apr pull` uses pacha, which caches as:
     ~/.cache/pacha/models/<sha>.safetensors
     ~/.cache/pacha/models/<sha>.tokenizer.json
     ...
   not HF hub's snapshots/<sha>/ directory structure.

3. apr distill --backend cuda calls CudaTrainerTeacher::for_inference
   which expects a directory containing model.apr or model.safetensors.
   The pacha cache is a flat file. Need to symlink-stage into a dir.

Fixes:
- GX10_RUN_PREFIX env var (default $HOME/runs)
- New stage_repo() shell function inside SSH heredoc that:
  - captures `apr pull` Path: from stdout
  - mkdirs RUN_DIR_REMOTE/teacher and /student stage dirs
  - symlinks pacha-cached files as model.<ext>
  - symlinks companion tokenizer.json / config.json / tokenizer_config.json
  - for GGUF teachers, runs apr import --preserve-q4k to convert to APR
- Default TEACHER_REPO changed to Qwen/Qwen2.5-Coder-1.5B-Instruct
  (SafeTensors, loads directly into CudaTrainerTeacher). The original
  paiml/qwen2.5-coder-7b-apache-q4k-v1 (GGUF) needs the apr import
  conversion path, which works but is slow and disk-intensive on gx10
  (58GB free). Defer real-MODEL-1 dispatch to PMAT-698e after smoke
  validates the pipeline.

Test plan:
- [x] DRY_RUN=1 STEPS=50 bash scripts/...  exits cleanly
- [x] bashrs lint: 11 errors (pre-existing heredoc/string mis-parses, no
      regression)
- [ ] STEPS=50 dispatch on gx10 reaches the training loop (verified
      live via the PR description, not in CI since this is a script)

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

…98d cont.)

Second live-dispatch attempt revealed another defect: apr distill --backend
cuda reads teacher_path AS A FILE via std::fs::read + AprV2Reader::from_bytes,
THEN uses its parent directory for for_inference. Two expectations are tied
together:

  - the file at teacher_path must be a valid APR v2 binary (for metadata)
  - the parent directory must contain a loadable checkpoint (model.apr
    or model.safetensors) for CudaTransformerTrainer

The previous staging symlinked .safetensors at stage_dir/model.safetensors
which satisfied for_inference but failed the AprV2Reader read step
(symlink target had wrong magic bytes).

Fix: always run `apr import` (with --preserve-q4k for GGUF) to produce a
real APR v2 file at stage_dir/model.apr. The teacher_path passed to apr
distill is that .apr file. Its parent dir is the stage dir, which now
satisfies both expectations.

Also rename the dispatch output from student.apr to student-trained.apr
to disambiguate from the staged input checkpoints.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>