Add low_cpu_ram config to qlora recipes configs (excluding 2B/13B/70B configs)

[mikaylagawarecki]

Context

What is the purpose of this PR? Is it to

• add a new feature
• fix a bug
• update tests and/or documentation
• other (please add here)

Addresses this comment https://github.com/pytorch/torchtune/pull/1315/files#r1750554790

Changelog

What are the changes made in this PR?
Update all qlora recipes to have low_cpu_ram config option added in #1315

Test plan

colab notebook https://colab.research.google.com/drive/14fGovrKguuTh67T0eL_rIg7gmJVaYSie?usp=sharing that tests checkpoint save with and without low_cpu_ram and verifies that with low_cpu_ram=True all of the qlora recipes updated here no longer OOM on checkpoint save.

Please make sure to do each of the following if applicable to your PR. (If you're not sure about any one of these just ask and we will happily help. We also have a contributing page for some guidance on contributing.)

• run pre-commit hooks and linters (make sure you've first installed via pre-commit install)
• add unit tests for any new functionality
• update docstrings for any new or updated methods or classes
• run unit tests via pytest tests
• run recipe tests via pytest tests -m integration_test
• manually run any new or modified recipes with sufficient proof of correctness
• include relevant commands and any other artifacts in this summary (pastes of loss curves, eval results, etc.)

UX

If your function changed a public API, please add a dummy example of what the user experience will look like when calling it.
Example of docstring:

torchtune/torchtune/modules/vision_transformer.py

Line 285 in 6a7951f

Examples:

Example in our docs: https://pytorch.org/torchtune/main/tutorials/qat_finetune.html#applying-qat-to-llama3-models

• I did not change any public API;
• I have added an example to docs or docstrings;

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/torchtune/1580

• 📄 Preview Python docs built from this PR

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✅ No Failures

As of commit 38b274d with merge base ee343e6 ():
💚 Looks good so far! There are no failures yet. 💚

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[codecov-commenter]

Codecov Report

Attention: Patch coverage is 58.33333% with 5 lines in your changes missing coverage. Please review.

Project coverage is 71.05%. Comparing base (ee343e6) to head (38b274d).

Files with missing lines	Patch %	Lines
torchtune/models/mistral/_component_builders.py	33.33%	2 Missing ⚠️
torchtune/models/gemma/_component_builders.py	50.00%	1 Missing ⚠️
torchtune/models/llama2/_component_builders.py	66.66%	1 Missing ⚠️
torchtune/models/llama3_1/_component_builders.py	50.00%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1580      +/-   ##
==========================================
- Coverage   73.08%   71.05%   -2.03%     
==========================================
  Files         289      289              
  Lines       14157    14170      +13     
==========================================
- Hits        10346    10068     -278     
- Misses       3811     4102     +291     

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

[joecummings]

@ebsmothers

[ebsmothers]

Sorry for the long delay in getting to this one. This looks great!