GitLab

* dataset card initial

* few fixes

* adds groups for math, mmlu, gpqa

* added summary agrs

* moved sanitize_list to utils

* readme update

* recreate metadata moved

* multiple model support

* results latest split fix

* readme update and small refactor

* fix grouping

* add comments

* added pathlib

* corrected pathlib approach

* check whether to create a metadata card

* convert posix paths to str

* default hf org from token

* hf token value error

* Add logs after successful upload

* logging updates

* dataset card example in the readme

---------
Co-authored-by: Nathan Habib <nathan.habib@huggingface.com>
Co-authored-by: Alina Lozovskaia <alinailozovskaya@gmail.com>

* Higher is better tickers in output table

* add extra check for `higher_is_better` not being None already

* Update lm_eval/evaluator.py

* fixup format I messed up

* add comment (and retrigger tests)

---------
Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com>
Co-authored-by: haileyschoelkopf <hailey@eleuther.ai>

* [HFLM]Add support for Ascend NPU
Co-authored-by: jiaqiw09 <jiaqiw960714@gmail.com>
Co-authored-by: zhabuye <2947436155@qq.com>

* bump accelerate dependency version to 0.26.0 for NPU compat.

---------
Co-authored-by: jiaqiw09 <jiaqiw960714@gmail.com>
Co-authored-by: zhabuye <2947436155@qq.com>
Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com>

* Reorder vllm imports in vllm_causallms.py

* Update vllm_causallms.py

* rename lm_eval.logging module

* fix evaluation tracker args

* edit process multiple-choice

* split template yaml

* remove

* modified multiple_choice tasks

* udpate

* Update multiple_choice_template_b_yaml

* Update multiple_choice_template_a_yaml

---------
Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com>

* add mmlu tasks from pile-t5

* Update _mmlu_flan_cot_fewshot_template_yaml

* Update _mmlu_flan_cot_zeroshot_template_yaml

* Update _mmlu_flan_generative_template_yaml

* Update _mmlu_flan_loglikelihood_template_yaml

* Update _default_template_yaml

---------
Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com>

* add handling for bootstrap_iters=0 case

* add more detail to docstring

* run precommit

`gold_one_hot` needs to follow the dimension of predictions so that it still works when `--limit` is used and the indexes in gold does not cover all gold indexes.

* resize model embeddings

* resize only

* tokenizer help

* load tokenizer before model

* add comment and run precommit lint

* Add log message
Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com>

---------
Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com>

* Add tinyBenchmarks

* Add acknowledgements

* Add ordering of outputs for data-parallel

* Run pre-commit

* Add few_shot specifications

* Add tinyBenchmarks post-processing

* add conditional import ; fix task names

---------
Co-authored-by: haileyschoelkopf <hailey@eleuther.ai>

* add copal

* change name to copal id for clarity and the task name

* remove `copal_id...` to yaml to make it work

* checkmark on README

* change group name to `copal_id`

* add mmlu arc style evaluation

* rename arc_style to continuation

---------
Co-authored-by: Jonathan Burdge <jburdge@mahti-login11.mahti.csc.fi>
Co-authored-by: Jonathan Burdge <jburdge@mahti-login12.mahti.csc.fi>

* Initial support for Unitxt datasets in LM Eval Harness

See  https://github.com/IBM/unitxt



The script 'generate_yamls.py' creates LM Eval Harness yaml files corresponding to Unitxt datasets specified in the 'unitxt_datasets' file.

The glue code required to register Unitxt metrics is in 'unitxt_wrapper.py'.

* Added dataset loading check to generate_yaml

Improved error messages.

* Speed up generate_yaml

Added printouts and improved error message

* Added output printout

* Simplified integration of unitxt datasets

Store all the common yaml configuration in a yaml include shared by all datasets of the same task.

* Post code review comments - part 1

1. Made sure include files don't end wth 'yaml' so they won't be marked as tasks
2. Added more datasets and tasks (NER, GEC)
3. Added README

* Post code review comments - part 2

1. Added install unitxt install option in pyproject.toml:
pip install 'lm_eval[unitxt]'
2. Added a check that unitxt is installed and print a clear error message if not

* Commited missing pyproject change

* Added documentation on adding datasets

* More doc changes

* add unitxt extra to readme

* run precommit

---------
Co-authored-by: haileyschoelkopf <hailey@eleuther.ai>

* fix auto-batch size bug for seq2seq models

* alphabetize task + group tables ; fix eval tracker bug

* fix eval tracker bug

* add Hendrycks MATH (no sympy checking) variant

* add readmes for MATH tasks

* Added fewshot sampling seeds to evaluator.simple_evaluate signature

Way to control seed of fewshot sampling
may help with #1591

* Added ability for custom sampler for ConfigurableTask

May be set in config like
```
fewshot_config:
  sampler: !function utils.MyFewshotSampler
```

* explicitly set fewshot random generator seed for HFLM generate_until_task test

* add backward compatibility for three args seed setup

* save seeds info to logs/reports

* remove echo parameter in OpenAI completions API

* remove context length parameter doc string

* evaluation tracker implementation

* OVModelForCausalLM test fix

* typo fix

* moved methods args

* multiple args in one flag

* loggers moved to dedicated dir

* improved filename sanitization

* Add option to set OpenVINO config

* Use utils.eval_logger for logging

* vllm lora support

* remove print

* version check, rename lora kwarg

* upload new tasks

* add readmes

* run linters

---------
Co-authored-by: haileyschoelkopf <hailey@eleuther.ai>

* Update utils.py

This is a 4-choice task, option_e is null for all but 3 samples

* Fix options

Adaptive choices

* add option e

* bump multilingual arc version

---------
Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com>

* Add Pile-10k readme

* Add Pile-10k task configuration file

* Add register_filter decorator

* Add register_filter docs

* Support individual scrolls datasets

* Add qmsum context

* Fix formatting

* Update task.py

* Update __init__.py

* add xnli_eu tasks

* update tasks readme

* update readme

* Add neuralmagic models for SparseML and DeepSparse

* Update to latest and add test

* Format

* Fix list to List

* Format

* Add deepsparse/sparseml to automated testing

* Update pyproject.toml

* Update pyproject.toml

* Update README

* Fixes for dtype and device

* Format

* Fix test

* Apply suggestions from code review
Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com>

* Address review comments!

---------
Co-authored-by: Hailey Schoelkopf <65563625+haileyschoelkopf@users.noreply.github.com>