Refactor: Clean up EAGLE training dataset preparation

[benchislett]

What does this PR do?

Type of change: Refactor

Overview:

• Consolidate input dataset preparation into make_dataset.py
• Read dataset mix spec from a YAML file
• • Can now specify how many samples to take from each split
• • Can no longer easily split a dataset into train/test sections. I don't think this feature was really useful to begin with. Most datasets can already be separated into train/val/test at the split level, and those that can't are usually going to be splitted by the training FW anyways.
• Add support for a few new dataset types, magpie 300k/500k/1M, nemotron post-training dataset v2.

Usage

See README for detailed example

Testing

Ran it locally on all dataset modes, works successfully and output looks good. Checked shuffling, conversation IDs, and output contents were all unique and usable.

• Make sure you read and follow Contributor guidelines and your commits are signed.
• Is this change backward compatible?: Yes
• Did you write any new necessary tests?: No
• Did you add or update any necessary documentation?: Yes
• Did you update Changelog?: No

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 74.78%. Comparing base (47c04d6) to head (413f123).
⚠️ Report is 6 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #684      +/-   ##
==========================================
+ Coverage   74.47%   74.78%   +0.30%     
==========================================
  Files         183      192       +9     
  Lines       18415    18814     +399     
==========================================
+ Hits        13715    14070     +355     
- Misses       4700     4744      +44     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.