[tiny] cleanup logs & warnings

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- Ignore some of the expected logs and warnings that pollute stdout (e.g. triton not available on mac)
- In debug mode, everything is still logged

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October updates in README

Added October Oumi updates to README


Bump omegaconf from 2.4.0.dev3 to 2.4.0.dev4

Bumps [omegaconf](https://github.com/omry/omegaconf) from 2.4.0.dev3 to 2.4.0.dev4.

Release notes

Sourced from omegaconf's releases.

OmegaConf 2.4.0dev4

Final pre-release, barring bug reports/fixes, before stable release of OmegaConf 2.4.0

Commits

See full diff in compare view

[![Dependabot compatibility score](https://dependabot-badges.githubapp.com/badges/compatibility_score?dependency-name=omegaconf&package-manager=pip&previous-version=2.4.0.dev3&new-version=2.4.0.dev4)](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores)

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Update bitsandbytes requirement from <0.48,>=0.47 to >=0.47,<0.49

Updates the requirements on [bitsandbytes](https://github.com/bitsandbytes-foundation/bitsandbytes) to permit the latest version.

Release notes

Sourced from bitsandbytes's releases.

0.48.2

What's Changed

Fix indexing overflow issue for blockwise quantization by @matthewdouglas in bitsandbytes-foundation/bitsandbytes#1784

Fix regression with CPU/disk offloading for accelerate + int8 by @matthewdouglas in bitsandbytes-foundation/bitsandbytes#1786

XPU: Add Windows build for SYCL kernels by @matthewdouglas in bitsandbytes-foundation/bitsandbytes#1787

Full Changelog: https://github.com/bitsandbytes-foundation/bitsandbytes/compare/0.48.1...0.48.2

Changelog

Sourced from bitsandbytes's changelog.

v0.45.1

Improvements:

Compatibility for triton>=3.2.0

Moved package configuration to pyproject.toml

Build system: initial support for NVIDIA Blackwell B100 GPUs, RTX 50 Blackwell series GPUs and Jetson Thor Blackwell.

Note: Binaries built for these platforms are not included in this release. They will be included in future releases upon the availability of the upcoming CUDA Toolkit 12.7 and 12.8.

Bug Fixes:

Packaging: wheels will no longer include unit tests. (#1478)

Dependencies:

Sets the minimum PyTorch version to 2.0.0.

0.45.0

This is a significant release, bringing support for LLM.int8() to NVIDIA Hopper GPUs such as the H100.

As part of the compatibility enhancements, we've rebuilt much of the LLM.int8() code in order to simplify for future compatibility and maintenance. We no longer use the col32 or architecture-specific tensor layout formats while maintaining backwards compatibility. We additionally bring performance improvements targeted for inference scenarios.

Performance Improvements

This release includes broad performance improvements for a wide variety of inference scenarios. See this X thread for a detailed explanation.

Breaking Changes

🤗PEFT users wishing to merge adapters with 8-bit weights will need to upgrade to peft>=0.14.0.

Packaging Improvements

The size of our wheel has been reduced by ~43.5% from 122.4 MB to 69.1 MB! This results in an on-disk size decrease from ~396MB to ~224MB.

Binaries built with CUDA Toolkit 12.6.2 are now included in the PyPI distribution.

The CUDA 12.5.0 build has been updated to CUDA Toolkit 12.5.1.

Deprecations

A number of public API functions have been marked for deprecation and will emit FutureWarning when used. These functions will become unavailable in future releases. This should have minimal impact on most end-users.

The k-bit quantization feature


[bug] remove unsupported assignee in dependabot config

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- dependabot assignee cannot be a team. removing for now

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Deprecate experimental cambrian model

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- Deprecate experimental cambrian model

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[tiny] Allow trl 0.24 to unblock python 3.9 support

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- trl 0.25 dropped support for python 3.9
- to unblock python 3.9 users, this PR updates the trl dependency to include 0.24

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Update wandb requirement from <0.22,>=0.21 to >=0.21,<0.24

Updates the requirements on [wandb](https://github.com/wandb/wandb) to permit the latest version.

Release notes

Sourced from wandb's releases.

v0.23.0

What's Changed

Added

Experimental wandb beta leet command - Lightweight Experiment Exploration Tool - a terminal UI for viewing W&B runs locally with real-time metrics visualization and system monitoring (@dmitryduev in wandb/wandb#10764)

The registry API now supports programmatic management of user and team members of individual registries. (@tonyyli-wandb in wandb/wandb#10542)

Registry.id has been added as a (read-only) property of Registry objects (@tonyyli-wandb in wandb/wandb#10785).

Fixed

Artifact.files() now has a correct len() when filtering by the names parameter (@matthoare117-wandb in wandb/wandb#10796)

The numerator for file upload progress no longer occasionally exceeds the total file size (@timoffex in wandb/wandb#10812)

Artifact.link() now logs unsaved artifacts instead of raising an error, consistent with the behavior of Run.link_artifact() (@tonyyli-wandb in https://github.com/wandb/wandb/10822)

Automatic code saving now works when running ipython notebooks in VSCode's Jupyter notebook extension (@jacobromero in wandb/wandb#10746)

Logging an artifact with infinite floats in Artifact.metadata now raises a ValueError early, instead of waiting on request retries to time out (@tonyyli-wandb in wandb/wandb#10845).

Changelog

Sourced from wandb's changelog.

[0.23.0] - 2025-11-11

Added

Experimental wandb beta leet command - Lightweight Experiment Exploration Tool - a terminal UI for viewing W&B runs locally with real-time metrics visualization and system monitoring (@dmitryduev in wandb/wandb#10764)

The registry API now supports programmatic management of user and team members of individual registries. (@tonyyli-wandb in wandb/wandb#10542)

Registry.id has been added as a (read-only) property of Registry objects (@tonyyli-wandb in wandb/wandb#10785).

Fixed

Artifact.files() now has a correc


Update safetensors requirement from <0.7,>=0.6 to >=0.6,<0.8

Updates the requirements on [safetensors](https://github.com/huggingface/safetensors) to permit the latest version.

Release notes

Sourced from safetensors's releases.

v0.7.0

What's new

complex64 support

This release adds support for storing complex64 tensors.

What's Changed

Revert "Early bailing when keys mismatch (faster). (#602)" by @Narsil in huggingface/safetensors#647

Support using paddle in safe_open by @zeroRains in huggingface/safetensors#630

Fix clippy lint. by @Narsil in huggingface/safetensors#648

Support paddle save/load/save_file/load_file without coverting to numpy by @changeyoung98 in huggingface/safetensors#646

Fix no-std feature configuration to auto-fallback from std to alloc by @antimora in huggingface/safetensors#651

Fix big endian (S390X) test by @danieldk in huggingface/safetensors#654

Fixing get_slice. by @Narsil in huggingface/safetensors#655

Update hashbrown dependency to 0.16 by @danieldk in huggingface/safetensors#658

Fix documentation build by @danieldk in huggingface/safetensors#667

Add packaging as a dependency for the torch extra by @danieldk in huggingface/safetensors#666

Support the complex64 data type by @danieldk in huggingface/safetensors#660

feat: add header size check at serialization by @McPatate in huggingface/safetensors#669

Set version to 0.7.0-dev.0 by @danieldk in huggingface/safetensors#670

Fix release CI issues by @danieldk in huggingface/safetensors#673

New Contributors

@zeroRains made their first contribution in huggingface/safetensors#630

@c


Bump the minor-and-patch group with 2 updates

Bumps the minor-and-patch group with 2 updates: [antlr4-python3-runtime](http://www.antlr.org) and [einops](https://github.com/arogozhnikov/einops).

Updates `antlr4-python3-runtime` from 4.11 to 4.13.2

Updates `einops` from 0.6.1 to 0.8.1

Release notes

Sourced from einops's releases.

v0.8.1 Multiple improvements

What's Changed

TLDR:

ellipsis is added to EinMix

tests moved into the package

devcontainer provided

added backend for pyTensor

niceties: citation, docs, fixed broken links

this did not require any changes in einops, but array API is supported by more libs these days, and einops can operate on them

PRs:

Update README.md by @project-delphi in arogozhnikov/einops#316

change tests for numpy2.0 + fix for numpy regression  by @arogozhnikov in arogozhnikov/einops#325

PR from @pzread: fix tinygrad concat + changed formatting to fix CI errors by @arogozhnikov in arogozhnikov/einops#329

Add devcontainer and dockerfile by @arogozhnikov in arogozhnikov/einops#330

delete experimental/indexing by @arogozhnikov in arogozhnikov/einops#333

Use same ruff version in CI and in pre-commit, reformat notebooks by @arogozhnikov in arogozhnikov/einops#336

Delete chainer backend by @arogozhnikov in arogozhnikov/einops#335

Mention support of cupy, pydata/sparse, ndonnx and others by @arogozhnikov in arogozhnikov/einops#337

Moving tests into source tree by @arogozhnikov in arogozhnikov/einops#338

Update documentation, mention changes in testing + devcontainers by @arogozhnikov in arogozhnikov/einops#339

Auto-deploy mkdocs + update mkdocs requirements by @arogozhnikov in arogozhnikov/einops#341

Add dict syntax to the einops layers example by @eadadi in arogozhnikov/einops#342

include CITATION.cff for einops by @luke-carlson in arogozhnikov/einops#345

mention that cupy and jax now support array api by @arogozhnikov in <a href="htt


Bump the all-actions group with 5 updates

Bumps the all-actions group with 5 updates:

| Package | From | To |
| --- | --- | --- |
| [actions/checkout](https://github.com/actions/checkout) | `4` | `5` |
| [astral-sh/setup-uv](https://github.com/astral-sh/setup-uv) | `2` | `7` |
| [actions/setup-python](https://github.com/actions/setup-python) | `5` | `6` |
| [docker/build-push-action](https://github.com/docker/build-push-action) | `5` | `6` |
| [google-github-actions/auth](https://github.com/google-github-actions/auth) | `2` | `3` |

Updates `actions/checkout` from 4 to 5

Release notes

Sourced from actions/checkout's releases.

v5.0.0

What's Changed

Update actions checkout to use node 24 by @salmanmkc in actions/checkout#2226

Prepare v5.0.0 release by @salmanmkc in actions/checkout#2238

⚠ Minimum Compatible Runner Version

v2.327.1

Release Notes

Make sure your runner is updated to this version or newer to use this release.

Full Changelog: https://github.com/actions/checkout/compare/v4...v5.0.0

v4.3.1

What's Changed

Port v6 cleanup to v4 by @ericsciple in actions/checkout#2305

Full Changelog: https://github.com/actions/checkout/compare/v4...v4.3.1

v4.3.0

What's Changed

docs: update README.md by @motss in actions/checkout#1971

Add internal repos for checking out multiple repositories by @mouismail in actions/checkout#1977

Documentation update - add recommended permissions to Readme by @benwells in actions/checkout#2043

Adjust positioning of user email note and permissions heading by @joshmgross in actions/checkout#2044

Update README.md by @nebuk89 in actions/checkout#2194

Update CODEOWNERS for actions by @TingluoHuang in actions/checkout#2224

Update package dependencies by @salmanmkc in actions/checkout#2236

Prepare release v4.3.0 by @salmanmkc in actions/checkout#2237

New Contributors

@motss made their first contribution in actions/checkout#1971

<a href="https://github.co


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- Add github action to manage stale issues / PRs

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Update github actions runs on config

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- `merge_group` does not support `paths`, unlike `pull_request`
- Re-enable some tests to run on PRs: `docs`, `install`

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[nit] run yaml linter on github config files

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- Run yaml linter on github config files
- No logic change, just linting

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Add dependabot config

# Description

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- Add dependabot config

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[tiny] fix lint error on readme.md

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- [tiny] fix lint error on readme.md

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Fix docker release action

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- The `docker_release` github action is running into disk space limits of the github VMs (~14GB available)
  - Upgrading to larger VM did not help as they all have the same disk quota
- This PRs adds a step to clear some unused files to allow for the image to build.
  - Found this trick on this [blog](https://carlosbecker.com/posts/github-actions-disk-space/)
- Tested here: https://github.com/oumi-ai/oumi/pkgs/container/oumi

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Added news item on OpenEnv notebook

See title


enable custom master port for distributed training

# Description

The Pytorch distributed port is hard coded as 8007 ( _DEFAULT_MASTER_PORT ) and can not be changed when using Slurm or Polaris scheduler. However, due to some internal/entreprise restriction, this port might be unavailable.
It should be possible to use the 'classical' environement variable MASTER_PORT defined in Pytorch for more flexibility

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# Solution
The changes in the code is to use the existing code from the local machine process

`master_port=int(env.get(_MASTER_PORT_ENV, _DEFAULT_MASTER_PORT))`

If the environement is not set, we fall back to the default value  = 8007
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[bug] Fix oumi distributed on Slurm to use correct node rank env var

# Description

In `oumi distributed`, we set the node rank to the value of `SLURM_PROCID` or `PMI_RANK`. However, this only works if the user specifies 1 task per node for the Slurm job, and will crash otherwise. This PR instead uses `SLURM_NODEID`, which correctly reflects the node id. Tested on Exun and Perlmutter.

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# Description

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- [docs] add documentation page for oumi tune

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[bug] Fix oumi distributed slurm node list bug

# Description

Our previous logic didn't expand Slurm's nodelist format out properly in the case of multiple nodes. This PR fixes that by using the recommended utility `scontrol show hostnames`. Tested this change on Exun, Frontier and Perlmutter.

## Related issues

Fixes #2015

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[bug] add tune target to ci_gpu

# Description

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- While `tune` is optional, it is still needed to run the tune integration tests

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[docs] add/update docs for v0.5 release

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- [docs] add/update docs for v0.5 release

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[tune] make optuna import optional

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- Make optuna import optional since it's not part of the default dependencies

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Update OpenEnv notebook with reward graph

notebooks/Oumi - OpenEnv GRPO with trl.ipynb

# Description

- Add instructions for enabling wandb
- Increase max completion length

## Related issues

Fixes OPE-1762

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deps: Upgrade trl to 0.25

# Description

Ran e2e tests.

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Updated SLURM process environment variable: replaced PMI_RANK with SLURM_PROCID

# Description
While using the Oumi distributed wrapper, I encountered an issue where processes failed to establish a rendezvous. After investigating the code, I found that during the detection of the slurm process run info (`_detect_slurm_process_run_info)`, the wrapper was assigning the wrong node_rank. It used the environment variable PMI_RANK instead of SLURM_PROCID.

# Solution
- Use either `SLURM_PROCID` or `PMI_RANK` to set the node rank in multi-node setups.
- For single-node setups, the node rank is automatically set to 0.
- Raise an error if `node_rank` is not set in multi-node setups, since it is mandatory for `torchrun`.
## Related issues
#2007

Fixes # (issue)

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[bug] fix issue initializing gkd trainer

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- Fix bug initializing the gkd trainer, where dtype was missing in some cases
- Add unit tests
- Switch from `torch_dtype` to `dtype`, as the former is getting deprecated

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# Description

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I ran into a backwards compatibility issue with these fields. This should fix it by making them optional params.
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- Made chat_template_kwargs and image_id_map fields optional for backwards compatibility

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Add call to action to all Oumi notebooks

notebooks/Oumi - Build your own Custom Evaluation (Hallucination Classifier).ipynb

notebooks/Oumi - Bulk Inference of LLM APIs.ipynb

notebooks/Oumi - Distill a Large Model.ipynb

notebooks/Oumi - Evaluation with AlpacaEval 2.0.ipynb

notebooks/Oumi - Evaluation with MT Bench.ipynb

notebooks/Oumi - Evaluation with Oumi.ipynb

notebooks/Oumi - Finetuning Tutorial.ipynb

notebooks/Oumi - Launching Jobs on Custom Clusters.ipynb

notebooks/Oumi - Quantization Tutorial.ipynb

notebooks/Oumi - Running Jobs Remotely.ipynb

notebooks/Oumi - Train a Letter Counting Model using GRPO.ipynb

notebooks/Oumi - Training CNN on Custom Dataset.ipynb

notebooks/Oumi - Using vLLM Engine for Inference.ipynb

notebooks/Oumi - Vision Language Models.ipynb

# Description

Mentions GitHub, Substack, Youtube, and Oumi Platform.

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- [bug] add default torch_dtype value required gkd trainer

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Upgrade trl to 0.24.0

# Description

Tested with E2E and GPU tests

## Related issues

Towards OPE-1762

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Update Qwen3 VL 4b_instruct_fft_train.yaml


Add tuning module for hyperparameter search/tuning

# Description
This PR is the start of a module to run hyperparameters tuning inside oumi.
With the changes here, I hope to implement the core foundations to use oumi to run a hyperparameter study (with SFT at first).
I hope to use Optuna together with oumi to orchestrate the study.

## Related issues
_This PR fixes an issue I've opened a few days ago regarding my interest in developing a new hyperparameter tuning module for oumi._

Fixes #1984

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Improve error raising for document processing issues

# Description

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Lazy init clouds in oumi launcher

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- Some cloouds have a non hermetic init, which can cause issues in some situations (e.g. air-gapped environments or temporal worfklows)+ slows down the overall launch
- This PR skips initializing all the clouds at startup. Instead they are lazily initialized as needed

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Refactor analyze

# Description
Refactor Analyze to make it more general and able to analyze any dataset:
* Data is modeled as pandas dataframes, it allows repeated keys (unlike a dict)
* Analyzers with Dataframes allow having any number of columns to be analyzed. Schema will define what these columns are
* It can analyze different types of content: text, float, timestamp, object, ... which will be defined for each column in the schema
* Analyzers are now agnostic to the dataset object's logic. they only take a dataframe and a schema
* Analyzers can join multiple dataframes based on the join_on columns passed to them. Nested messages can be handled this way. For example message level dataframe and conversation level dataframe

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Towards LOU-12

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Update uv pip install commands to include --system

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E2E tests are failing now due to a message suggesting to use `uv venv` or `--system`. Updating pip installs to use `--system` which aligns with how our workflow tests run.
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Pin uvicorn version to fix skypilot

# Description

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Uvicorn 0.36.0 made a breaking change for skypilot that has yet to be addressed, pinning <0.36.0 to fix.
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Make stdout_file optional in slurm client

# Description

Updates the type annotation for the `stdout_file` parameter in `SlurmClient.submit_job` from `str` to `Optional[str]`. This change correctly reflects that the parameter can be `None`, aligning with other optional parameters in the method signature.

## Related issues

Fixes #OPE-1555

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---
Linear Issue: [OPE-1555](https://linear.app/oumi/issue/OPE-1555)

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# Description
extract conversation_turns from conversation_level_summary to top level

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Update README.md

# Description

- Mention 0.4.0 release
- Add mentions of new trainers
- Update list of supported models


Fixed Sky Pilot Unit Tests Failing

# Description

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There was a regression from this PR (https://github.com/oumi-ai/oumi/pull/1951) where it broke unit tests even though it still got merged into main. This PR fixes the sky pilot failing unit tests based on the new mocks we needed for the upgraded sky pilot version.
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Fixes OPE-1531

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[tiny] Upgrade transformers to 4.56

# Description

Upgade to latest version. Confirmed E2E tests pass, and made minor changes

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Fix NaN values in dataset analyzer statistics for single conversations

# Description
Std is set to 0 instead of NaN when aggregating a single item

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Penfever/llamacpp role fix

# Description

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Adding missing support for SYSTEM role in LlamaCPP engine inference.

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[tiny] Remove `add_special_tokens` kwarg from vision DPO dataset processor

# Description

This causes an error for Phi3 DPO because it's not a kwarg for the Phi3 processor: https://huggingface.co/microsoft/Phi-3-vision-128k-instruct/blob/main/processing_phi3_v.py#L58. It's not in the Qwen2 VL processor either: https://github.com/huggingface/transformers/blob/e3d8fd730ed063a88edc49ed5f3c8acfabb53368/src/transformers/models/qwen2_vl/processing_qwen2_vl.py#L93

## Related issues

Towards OPE-1524

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Follow-up updates to DeepSpeed PR

# Description

Misc. changes building on top of #1886, which added DeepSpeed support.

- Moved Limo configs to configs/projects/limo.
- Updated typing and documentation in DeepspeedParams

## Related issues

Fixes OPE-1513

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Run GitHub workflows in merge queue instead of on PR events

# Description

Currently, our test workflows are run whenever a PR is opened, synchronize, or reopened. This is eating into our quota. This PR instead has those tests run in a merge queue when the PR is submitted (with the exception of pretest.yaml, which we keep running for PR updates). The user is still able to run tests manually before the PR is submitted with the `workflow_dispatch` hook.

Documentation: https://docs.github.com/en/repositories/configuring-branches-and-merges-in-your-repository/configuring-pull-request-merges/managing-a-merge-queue
https://docs.github.com/en/actions/reference/workflows-and-actions/events-that-trigger-workflows#pull_request

## Related issues

Fixes OPE-1512

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Add The Ability To Trail Logs For Launcher Jobs

# Description

We currently have built-in support from SkyPilot for trailing logs through their SDK after launching a job. We want to extend this functionality to our other clusters as well.

This PR adds support for Slurm clusters by tailing the log file and streaming its contents directly to the user’s terminal. For clusters not covered in this PR, the behavior will remain unchanged and continue to show the loading spinner.

Features Added:
- Tailing logs is now supported in Slurm as an IOStream to our rich console
- Tailing logs is Sky Pilot is now returning an IOStream to our rich console
- Support for passing in an IO file for the logs to be streamed to works with the parameter "--output-filepath"
- Sky Pilot upgraded and patched to support streaming to a file

**BEFORE With Slurm**

**AFTER With Slurm**

**AFTER With Sky Pilot**

**After With Local Cluster**

## Related issues

Towards OPE-1344
Fixes #1735

## Before submitting

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Add a parsable enum state field to the launcher to convey job status

# Description

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Previously the oumi launcher only exposed a `done` enum, as well as a string for status parsing. This PR adds an enum `state` to easily check if a job is `pending`, `failed`, `succeeded`, or `cancelled`.

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Penfever/api and macos configs

# Description

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Adds config files for newer API and local models (GPT 5, Qwen 3, Claude Opus 4.1, Gemma 3)

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Update llama_cpp_inference_engine.py

# Description

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Change default LlamaCPP engine parameters for better memory management when running locally

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Add shell script for launching jobs on NERSC Perlmutter HPC cluster

# Description

This is similar to #1691, but for the Perlmutter cluster. Both use the Slurm scheduler, but Perlmutter has Nvidia GPUs and a slightly different setup for conda. Tested with `scripts/perlmutter/launcher.sh -u wizeng -d /global/homes/w/wizeng/oumi_launcher -j scripts/perlmutter/jobs/example_job.sh`.

## Related issues

Towards OPE-1507

## Before submitting

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[tiny] Update .gitignore

# Description

This is causing a bug with the Oumi launcher, because the oumi/src/oumi/models folder isn't being copied to remote clusters. We have output/ in the gitignore for storing model checkpoints.

## Before submitting

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Add Pre-Populated GitHub Issue Link On Failures

# Description

We want to make users more aware that when they run into any types of issues they should open an issue. This PR appends a pre-populated Github issue link after any type of failure occurs for the user to optionally open if they feel it should be tracked by the team.

Example: `oumi launch up -c configs/examples/grpo_verl_countdown/gcp_job.yaml --cluster grpo-verl-countdown`
**BEFORE CHANGES**

**AFTER CHANGERS**

**LONGER ERROR EXAMPLE**

NOTE: For any jobs used with the launcher, rich console logs that leverage links won't work. Instead a check is made and if its a remote job we just display the template for the user to use instead of populating any fields

## Before submitting
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Judge CLI | Display Overall Score

# Description

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**Judge CLI: Display Overall Score**

Output of command:
```
oumi judge conversations \
  --config truthfulness \
  --input <some path>/completions.jsonl
```
...is shown below (Overall Score: 50.00%):

<img width="1420" height="354" alt="image" src="https://github.com/user-attachments/assets/aedf7450-745c-4f71-8211-61067220b033" />

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Towards OPE-1327

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Replace mentions of deprecated `huggingface-cli` tool with `hf`

# Description

Example warning message:
```
⚠  Warning: 'huggingface-cli download' is deprecated. Use 'hf download' instead.
```

I did the following find-replaces in our codebase:
- `huggingface-cli download` -> 'hf download'
- `huggingface-cli login` -> 'hf auth login'
- `huggingface-cli upload-large-folder` -> 'hf upload-large-folder'

Additional code changes were made by the linter, not me.

## Before submitting

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Replace Luma link with YouTube recording for August webinar


Update README.md - updated after Aug webinar

Will replace Luma link with YouTube once the edited video is posted


Ryan arman add analysis summary

# Description
Adding computation of summary statistics for message level and conversation level
Also raises an exception when analysis results are not ready instead of silently calling analyze_dataset

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Fixes OPE-1496
Towards OPE-1370

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Update README.md to highlight `gpt-oss` support

The title says it all


[tiny] Cleanup redundant specifications of lora_dropout 0.0

# Description

In https://github.com/oumi-ai/oumi/pull/1124, we changed the default value of `lora_dropout` from 0.05 to 0. We can now clean up this field from our yaml configs to reduce bloat.

## Related issues

Towards OPE-1490

## Before submitting

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Improve e2e eval tests

# Description

- Replace eval task for multi-modal models from `mmmu_val` to `mmmu_val_computer_science` to be in line with `mmlu_college_computer_science` for non-MM models. This also reduces runtime for E2E tests.
- Delete redundant tests. We don't need to test Llama 1B/3B/8B all for eval if they're the same family.
- Add parameter to support using vLLM inference engine for eval
- Re-enable train_mm_llama3_2_vision_11b_full
- Reduce num steps to reduce runtime

Tested that all e2e tests pass

## Related issues

Towards OPE-1483

## Before submitting

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GGUF configs, MacOS LlamaCPP configs

# Description

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Add Oumi configs for GGUFs and the LlamaCPP engine, making it easier for users to understand how to run inference in Oumi using these model types.

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# Description

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- Deprecate experimental ring attention support
- This is causing issues with the latest flash-attn / transformers version. Removing since unused.

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Add august webinar to the readme.

# Description

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Add the August webinar link to our README.

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Unpin `flash-attn` version

# Description

Since we upgraded the PyTorch version, the pinned flash-attn version 2.7.4.post1 doesn't have a prebuilt wheel and has to be built from source. Tested that the error we previously encountered about an unknown symbol doesn't show up after unpinning.

Tested with e2e tests.

## Related issues

Towards OPE-1336

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Modify document ingestion to read bytes

# Description

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