Documentation: Judge | 1st revision (of many)

# Description

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1) Re-written most of the main page
- Intro: Done
- Overview: Done
- When to Use? Done
- Oumi Offerrings: Done
- Built-In Judge: _NEEDS REVISION_
- Custom Judges: _NEEDS REVISION_

2) Refactored the structure
- Judges Court page --> Renamed to `built_in_judge`; now **_only_** focusing on our built-in judge
- Custom Judges --> refactored and broke down...
   Intro: Adapted and moved to main page (`judge.md`)
   Level 1: Moved to `custom_prompt.md`
   Level 2: Moved to `custom_infer.md`
   Level 3: Deleted

What's next?
- Revise: `judge.md` / Built-In Judge
- Revise: `judge.md` / Custom Judges
- Revise: `custom_prompt.md`
- Revise: `custom_infer.md`
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Update quickstart.md with emoji

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Remove some notebook E2E tests

notebooks/Oumi - Evaluation with AlpacaEval 2.0.ipynb

notebooks/Oumi - Finetuning Tutorial.ipynb

notebooks/Oumi - Launching Jobs on Custom Clusters.ipynb

# Description

This PR removes notebooks which are too expensive/slow to run for E2E tests (ex. they call GPT-4, they start a remote instance). In addition, it restores cell outputs for many of our notebooks.

## Related issues

Towards OPE-713

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Add a Customizing Oumi page to our docs

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I've added a `Customizing Oumi` page in our `User Guides` section:
<img width="1676" alt="image" src="https://github.com/user-attachments/assets/a0cc08db-2e74-4888-aeda-5330dbaf21e0" />

This page covers which classes you can register in the Oumi Registry, as well as how to set our environment variables to use them via the CLI.

Additionally, I updated most `Custom ...` pages to point to this tutorial for using the CLI.
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Fixes OPE-865

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[tiny] Looser pandas version requirements

# Description

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- The pandas API is very stable, the current constraints is a little bit too strict. Updating to avoid env conflicts

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Get all notebooks to run

notebooks/Oumi - Evaluation with MT Bench.ipynb

notebooks/Oumi - Running Jobs Remotely.ipynb

notebooks/Oumi - Using vLLM Engine for Inference.ipynb

scripts/polaris/notebooks/Oumi - Multinode Inference on Polaris.ipynb

# Description

Notebooks are now bug-free, but additional work is still required to let them run in an automated fashion, and to make them run in under 10 min. For example:
- Some notebooks have runnable cells that spawn GCP nodes, with the expectation that the rest of the notebook is run on GCP
- vLLM inference loads Llama 70B by default, which takes awhile
- For me, the native inference engine on SmolLM 135M with one inference example is taking 3-6 minutes on my Mac. This is way too slow

## Related issues

Towards OPE-713

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VLM e2e integration tests update

# Description

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-- Add Qwen2 VL e2e test for OUMI trainer
-- Start using `pytest.skip()` for skipped tests
-- Disable wandb by default for tests
-- Add new params to test spec
-- Update OUMI trainer to empty CUDA cache before and after model/state saving (shouldn't hurt)

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Towards OPE-698

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Reduce batch size in Qwen2 VL eval config to reduce chances of OOM

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Update readme, first iteration

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- Update readme, first iteration

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Towards OPE-833

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Updated notebooks and quickstart documentation

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This update contains three changes.

1. Updated quickstart documentation to make the custom dataset code runnable, and to provide more options for launching distributed training.
2. Changed a line of text in the Oumi Finetuning Tutorial Notebook to more accurately reflect the state of the code and avoid potential confusion
3. Refactored YAML generation in the Oumi - A Tour notebook to allow for `tutorial_dir` to be set only once, at the beginning of the notebook.

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[docs] Add an entry for "Fine-tuning a Vision-Language Model"

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-- Add a top-level entry for "Fine-tuning a Vision-Language Model", and cross-link related docs for discoverability.

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Towards OPE-733

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[Documentation] Evaluate | Standardized Benchmarks page (refactor)

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Documentation: Evaluate | Standardized Benchmarks page (refactor)
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[docs] Add doc section for MMMU benchmark

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-- Add basic info about MMMU in docs/user_guides/evaluate/standardized_benchmarks.md

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Towards OPE-733

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Update sample VLM eval config

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-- Define eval config for Qwen2 VL w/ `MMMU`
-- Improve Llama 3.2 11B Vision Instruct eval config

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Towards OPE-733
Fixes OPE-649

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Update our documentation for custom clusters

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I removed one duplicate tutorial.
The custom cluster tutorial is almost a direct port of the previous notebook. The only addition is a few CLI commands and instructions on how to register the class for use in the CLI.
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Fixes OPE-860

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Remove `target_col: ` from VLM configs

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-- No longer required after https://github.com/oumi-ai/oumi/pull/1080
-- Tested OK with several models

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Towards OPE-812

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Review default values

# Description

Review our config's default values, and update some to a more reasonable value (or one that's equivalent to HF's defaults if we don't have a strong opinion).

## Related issues

Fixes OPE-819

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[docs] Multimodal SFT datasets: minor updates

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-- Call `@register_dataset` in custom dataset example
-- Add basic class docstrings for custom MM datasets.

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Towards OPE-733

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[docs] Add badges, smaller logos, and nit fix to notebook

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- Add badges, smaller logos, and nit fix to notebook

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Closes OPE-838, Towards OPE-828

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Fix a circular dependency when invoking the oumi src directory via Python.

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You will get a circular dependency error if you run the simple command:
```
python ./src/oumi
```

The reason here is a nuance of the import system. When running the above command, `/src/oumi` becomes the default directory from which packages are imported. Therefore running `import datasets` imports our `oumi.datasets` package instead of the global `datasets` 3rd party package we have installed. This leads to a circular dependency.

The simple solution is to move the first system path to the end of the system list when we detect oumi is being called in such a fashion.
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Fixes OPE-881

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Reorganize oumi distributed run logic

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- Reorganize oumi distributed run cli commands without any logic change
- Better isolate each environments logic, and clarify which variables are used for execution vs validation

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Closes OPE-879

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Update `oumi train` path to set `TOKENIZERS_PARALLELISM` variable

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-- Set `TOKENIZERS_PARALLELISM` and `ACCELERATE_LOG_LEVEL`  if not already configured to suppress scary-looking warning about forked process.

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Towards OPE-880

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Update quickstart.md

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Modified the quickstart output directory to reflect the current default -- added instructions that changing output directory might be necessary.

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[docs] address mic feedback from the team

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- Address mic feedback from the team

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[docs] Remove placeholder pages

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- Remove placeholder pages and sections, until they are ready to be added

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[docs] Update dataset formats page

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- First pass at cleaning up the dataset format page

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Towards OPE-809

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Set `rank/world_size/device_id=` params in `init_process_group()` to resolve warnings

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Set `torch.distributed.init_process_group(rank=..., world_size=..., device_id=...)` params, which resolved logs warnings like below:
```
 [rank2]:[W114 23:19:56.289295099 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 2]  using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id.
```

Started to see these warnings recently. The change eliminates them,  no other difference observed.

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Towards OPE-738

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Evaluation yaml configs: standardize task name

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Why am I doing this?

Goals:
- Standardize to a default `task_name` for all sample evaluation configs
- Choose a task name that executes in O(sec) on a MAC (vs. ~5mins ATM, for mmlu)
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Update the Deploy page to use CLI and python instructions.

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I've rewritten this tutorial to be strictly markdown. We no longer copy the notebook for deployment.
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Towards OPE-860
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Update training logging

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-- Log trainer type and `transformers` version for all trainers

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[docs] Refresh datasets resource page

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- Refresh datasets resource page

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Towards OPE-809

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[tiny] Upgrade minimum numpy version to unblock python3.12 installation

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- Upgrade minimum numpy version to unblock python3.12 installation
- More info [here](https://numpy.org/doc/2.1/reference/distutils_guide.html)
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Closes OPE-870

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Update our Readme with a new header image.

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Added a header image to the README.
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[docs] Minor refresh to dataset resource pages

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- Minor refresh to dataset resource pages
- Add description in the intro and fix renamed base classes

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Towards OPE-809

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[docs] Add docs guide page

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- Add docs guide page with instructions to edit and build the docs locally
- Copied @taenin & @wizeng23 's guide

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[Documentation] Evaluate | Main Page (small refactor)

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Evaluate | Main Page (small refactor)
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[docs] remove unused page, fix links

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- Fix include links in evaluation pages
- Remove git workflow page, moved to wiki

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# Description

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- Add GitHub Actions workflow for doctests
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[tiny] Fix precommit

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- Fix pre-commit

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# Description

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- Add timeout for unit & integration tests at 5min (the most time-consuming test takes less than 2min right now)
- The goal is prevent excessive CI resources usage (especially GPU checks). One recent PR contained a bug that let the tests run for multiple hours

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[Documentation] Evaluate | Main Page (revision)

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Documentation: Evaluate | Main Page (major revision)

**Core updates:**
1. Revised overview and converted it to a section of 5 bullet points motivating why users should use Oumi for their evaluations
2. Mentioned underlying platforms we are integrating with on the very top
3. Only kept the very basic yaml config and moved it to QuickStart. Everything else config-related went to a (new) dedicated page "Evaluation config"
4. Results and Logging: Broke it down to 3 subsections.
- Evaluation Results: Added more details regarding how our results look like (schema)
- Reproducibility Metadata: Highlighted & motivated more that Oumi evals are reproducible
- Weights & Biases: Added more context regarding what Wandb is and its importance.
5. (new) "Evaluation config" (=yaml) page
- Motivated a bit why we use yaml
- Added more configuration options (not all, that's impossible), including inference_engine and inference_remote_params.

(i) Addressed 90-95% of [Manos feedback](https://docs.google.com/document/d/13WKnBJG2y2SGPGlvl9QyYoG-WKS_pCOBi2XzD7SRpZk)

**Not done:**
- Updating the term "Standardized Benchmarks"
- Moving LM Harness generative benchmarks into Generative page (not relevant to this page though); Needs further scoping (from Kostas) and discussion with Oussama. Likely to postpone after launch.

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Remove `pytest.mark.skip()` for basic e2e tests

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-- I have no context on this  `@pytest.mark.skip ` but removing it seems like the right thing to do

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Towards OPE-698

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[Minor] Notebook typo

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[doc] Oumi Models (part-1)

# Description

Solidify exposure or Oumi models in Docs.

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[Super Nit Doc Update] environments.md

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Removing these dots. Dont look good.
https://oumi.ai/docs/latest/user_guides/train/environments/environments.html

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# Description

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- Add e2e tests for running tutorial notebooks

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Closes OPE-781

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[Doc > Quickstart] Should we add links to guides for better discoverability?

… discoverability?

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I was looking for a section on how to launch jobs and (surprisingly - no pan intended) I missed it.
Should we add one sentence at the end of Inference, Evaluation, Launching Jobs quickstart and link to the relevant user guide?
I know there are trade-offs here and this will increase the quickstart page's real-estate so... no strong opinion, just a suggestion.

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Specify `engine: NATIVE` is inference configs

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-- For clarity, let's have explicit engine specified .

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[tiny][docs] Update recipes page

# Description

Question: thoughts on deleting the inference section? It mostly repeats lines from the section above.

## Related issues

Towards OPE-810

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[Evaluation] HF Leaderboards yaml files

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Adding HF Leaderboards yaml files
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[tiny] [docs] troubleshooting improvements

# Description

- Tiny changes in the example:
set `max_grad_norm` to 0.5 since the default is 1
use `warmup_ratio` instead of `warmup_steps` since the former is agnostic to number of steps

- Added links to tokenizer, input data, and inference engines

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Define inference configs for more models

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-- Define inference configs for more VLM models, and add to README
-- Add missing entry for Llama 1B in README
-- Update docs to show how to use `oumi infer` for multimodal

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Towards OPE-733, OPE-862

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Replace assert in `NativeInferenceEngine` with `RuntimeError`

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-- For robustness. Shouldn't assert on model responses.

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Update dev set up instructions to use a Fork.

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- Removed instructions for installing the git CLI. We shouldn't need to tell users how to do this.
- Updated our dev instructions to use a fork + clone as this is what public contributors will need to do.
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## Before submitting

- [x] This PR only changes documentation. (You can ignore the following checks in that case)
- [ ] Did you read the [contributor guideline](https://github.com/oumi-ai/oumi/blob/main/CONTRIBUTING.md) Pull Request guidelines?
- [ ] Did you link the issue(s) related to this PR in the section above?
- [ ] Did you add / update tests where needed?

## Reviewers

At least one review from a member of `oumi-ai/oumi-staff` is required.

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