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feat: add huggingface post_training impl (#2132)

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# What does this PR do?


adds an inline HF SFTTrainer provider. Alongside touchtune -- this is a
super popular option for running training jobs. The config allows a user
to specify some key fields such as a model, chat_template, device, etc

the provider comes with one recipe `finetune_single_device` which works
both with and without LoRA.

any model that is a valid HF identifier can be given and the model will
be pulled.

this has been tested so far with CPU and MPS device types, but should be
compatible with CUDA out of the box

The provider processes the given dataset into the proper format,
establishes the various steps per epoch, steps per save, steps per eval,
sets a sane SFTConfig, and runs n_epochs of training

if checkpoint_dir is none, no model is saved. If there is a checkpoint
dir, a model is saved every `save_steps` and at the end of training.


## Test Plan

re-enabled post_training integration test suite with a singular test
that loads the simpleqa dataset:
https://huggingface.co/datasets/llamastack/simpleqa and a tiny granite
model: https://huggingface.co/ibm-granite/granite-3.3-2b-instruct. The
test now uses the llama stack client and the proper post_training API

runs one step with a batch_size of 1. This test runs on CPU on the
Ubuntu runner so it needs to be a small batch and a single step.

[//]: # (## Documentation)

---------

Signed-off-by: Charlie Doern <cdoern@redhat.com>
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Charlie Doern 2025-05-16 17:41:28 -04:00 • committed by GitHub
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requirements.txt
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@ -1,206 +1,69 @@
# This file was autogenerated by uv via the following command:
# uv export --frozen --no-hashes --no-emit-project --output-file=requirements.txt
annotated-types==0.7.0
# via pydantic
anyio==4.8.0
# via
# httpx
# llama-stack-client
# openai
attrs==25.1.0
# via
# jsonschema
# referencing
blobfile==3.0.0
# via llama-stack
cachetools==5.5.2
# via google-auth
certifi==2025.1.31
# via
# httpcore
# httpx
# kubernetes
# requests
charset-normalizer==3.4.1
# via requests
click==8.1.8
# via llama-stack-client
colorama==0.4.6 ; sys_platform == 'win32'
# via
# click
# tqdm
distro==1.9.0
# via
# llama-stack-client
# openai
durationpy==0.9
# via kubernetes
exceptiongroup==1.2.2 ; python_full_version < '3.11'
# via anyio
filelock==3.17.0
# via
# blobfile
# huggingface-hub
fire==0.7.0
# via llama-stack
fsspec==2024.12.0
# via huggingface-hub
google-auth==2.38.0
# via kubernetes
h11==0.16.0
# via
# httpcore
# llama-stack
httpcore==1.0.9
# via httpx
httpx==0.28.1
# via
# llama-stack
# llama-stack-client
# openai
huggingface-hub==0.29.0
# via llama-stack
idna==3.10
# via
# anyio
# httpx
# requests
jinja2==3.1.6
# via llama-stack
jiter==0.8.2
# via openai
jsonschema==4.23.0
# via llama-stack
jsonschema-specifications==2024.10.1
# via jsonschema
kubernetes==32.0.1
# via llama-stack
llama-stack-client==0.2.7
# via llama-stack
lxml==5.3.1
# via blobfile
markdown-it-py==3.0.0
# via rich
markupsafe==3.0.2
# via jinja2
mdurl==0.1.2
# via markdown-it-py
numpy==2.2.3
# via pandas
oauthlib==3.2.2
# via
# kubernetes
# requests-oauthlib
openai==1.71.0
# via llama-stack
packaging==24.2
# via huggingface-hub
pandas==2.2.3
# via llama-stack-client
pillow==11.1.0
# via llama-stack
prompt-toolkit==3.0.50
# via
# llama-stack
# llama-stack-client
pyaml==25.1.0
# via llama-stack-client
pyasn1==0.6.1
# via
# pyasn1-modules
# rsa
pyasn1-modules==0.4.2
# via google-auth
pycryptodomex==3.21.0
# via blobfile
pydantic==2.10.6
# via
# llama-stack
# llama-stack-client
# openai
pydantic-core==2.27.2
# via pydantic
pygments==2.19.1
# via rich
python-dateutil==2.9.0.post0
# via
# kubernetes
# pandas
python-dotenv==1.0.1
# via llama-stack
pytz==2025.1
# via pandas
pyyaml==6.0.2
# via
# huggingface-hub
# kubernetes
# pyaml
referencing==0.36.2
# via
# jsonschema
# jsonschema-specifications
regex==2024.11.6
# via tiktoken
requests==2.32.3
# via
# huggingface-hub
# kubernetes
# llama-stack
# requests-oauthlib
# tiktoken
requests-oauthlib==2.0.0
# via kubernetes
rich==13.9.4
# via
# llama-stack
# llama-stack-client
rpds-py==0.22.3
# via
# jsonschema
# referencing
rsa==4.9
# via google-auth
setuptools==75.8.0
# via llama-stack
six==1.17.0
# via
# kubernetes
# python-dateutil
sniffio==1.3.1
# via
# anyio
# llama-stack-client
# openai
termcolor==2.5.0
# via
# fire
# llama-stack
# llama-stack-client
tiktoken==0.9.0
# via llama-stack
tqdm==4.67.1
# via
# huggingface-hub
# llama-stack-client
# openai
typing-extensions==4.12.2
# via
# anyio
# huggingface-hub
# llama-stack-client
# openai
# pydantic
# pydantic-core
# referencing
# rich
tzdata==2025.1
# via pandas
urllib3==2.3.0
# via
# blobfile
# kubernetes
# requests
wcwidth==0.2.13
# via prompt-toolkit
websocket-client==1.8.0
# via kubernetes