feat(compressors): add JSONL training metrics logging with CLI controls

- Add write_training_metrics() in new compressors/training_metrics.py
  for appending epoch/step/lr/component rows as JSON Lines
- Wire --metrics-path and --log-every CLI options into train.py, passing
  them to the training loop so metrics rows are written every N steps
- Accept absolute metrics paths or paths relative to output directory
- Add quantization component to loss log alongside existing distill/contrastive
- Replace inline torch.device() with get_device() utility
- Add test_hash_training_metrics.py covering multi-row JSONL append

Infrastructure:
- Pin torch 2.7.1 + CUDA 12.8 index for Linux/Windows in pyproject.toml
- Add .justfile rsync upload recipe with .stignore exclusion
- Exclude **/__marimo__ from rsync in .stignore

Dependencies updated: numpy 2.4.5, pandas 3.0.3, black 26.5.0,
click 8.4.0, contourpy, etc.

.justfile

@@ -4,6 +4,12 @@ export MSYS2_ARG_CONV_EXCL := "*"
 export MSYS2_ENV_CONV_EXCL := "*"
 remote_ssh_target := env("REMOTE_SSH_TARGET")
 remote_docker_container := env("REMOTE_DOCKER_CONTAINER")
+remote_root := "$REMOTE_SSH_TARGET:$REMOTE_WORKDIR"
+rsync_flags := "-avLh --progress --stats --itemize-changes"
+upload_excludes := "--exclude-from=.stignore"
+
+upload:
+    rsync {{ rsync_flags }} {{ upload_excludes }} . {{ remote_root }}/; \
 
 sync-pkgs:
     uv sync --inexact