feat: generation options for infer.py, and split out training deps

infer.py could only render a random example from examples/input_params:
there was no way to pass your own prompt, lyrics, duration or seed, so
using it for anything specific meant writing a separate script. Add
--prompt, --lyrics/--lyrics_file, --duration, --steps, --guidance_scale,
--scheduler, --cfg_type, --omega_scale, --seed and --format alongside the
existing runtime flags. Without --prompt the old random-example behaviour
is kept, so existing invocations are unaffected.

Also move the training-only packages out of the default install.
datasets, pytorch_lightning, matplotlib, tensorboard and tensorboardX are
imported by trainer.py and convert2hf_dataset.py, never on the inference
path, but every user was installing them — and datasets==3.4.1 is a hard
pin that drags constraints onto huggingface-hub. They now live in
requirements-train.txt behind the existing (previously ineffective)
"train" extra: pip install -e ".[train]".

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

TRAIN_INSTRUCTION.md

@@ -1,5 +1,15 @@
 # Training Instruction
 
+## 0. Install the Training Dependencies
+
+Training needs a few packages that a plain inference install does not pull in
+(`datasets`, `pytorch_lightning`, `matplotlib`, `tensorboard`, `tensorboardX`).
+Install them with the `train` extra:
+
+```bash
+pip install -e ".[train]"
+```
+
 ## 1. Data Preparation
 
 ### Required File Format