Add LoRA and QLoRA Components, Models, and Configs for Phi3 Mini

[pbontrager]

Context

What is the purpose of this PR? Is it to

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

Please link to any issues this PR addresses.

Changelog

This PR extends the Phi3 Mini PR by adding the lora_phi3 class as well as lora_phi3_mini and qlora_phi3_mini model builders. This PR also introduces a new recipe configs: mini_lora, mini_lora_single_device, and mini_qlora_single_device.

Test plan

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.)

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

New Unit tests: Added a unit test for phi3 and for lora and qlora phi3 mini. These tests are a port of the llama2 tests. New configs: The 3 new configs so far are based off of llama2 and phi2 values. 1 epoch of training is being done now with:

tune run --nnodes 1 --nproc_per_node 2 lora_finetune_distributed --config phi3/mini_lora

tune run lora_finetune_single_device --config phi3/mini_qlora_single_device

tune run lora_finetune_single_device --config phi3/mini_lora_single_device

After runs are completed, this readme will be updated with loss and eval

[pytorch-bot[bot]]

:link: Helpful Links

:test_tube: See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/torchtune/932

• :page_facing_up: Preview Python docs built from this PR

Note: Links to docs will display an error until the docs builds have been completed.

:white_check_mark: No Failures

As of commit 2823b42747e4257cc6e02f033220c6860986e265 with merge base fa1392b08598202971a3afd291ec50bc35ceb342 (): :green_heart: Looks good so far! There are no failures yet. :green_heart:

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[codecov-commenter]

Codecov Report

Attention: Patch coverage is 98.91304% with 2 lines in your changes are missing coverage. Please review.

Project coverage is 66.14%. Comparing base (a978956) to head (c4ca183). Report is 26 commits behind head on main.

Files	Patch %	Lines
tests/torchtune/models/phi3/test_lora_phi3.py	99.15%	1 Missing :warning:
torchtune/models/phi3/_model_builders.py	80.00%	1 Missing :warning:

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #932      +/-   ##
==========================================
- Coverage   66.39%   66.14%   -0.26%     
==========================================
  Files         155      171      +16     
  Lines        6484     7165     +681     
==========================================
+ Hits         4305     4739     +434     
- Misses       2179     2426     +247     

:umbrella: View full report in Codecov by Sentry.
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[joecummings]

Actually approved now. Thanks @pbontrager