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+*.zstandard filter=lfs diff=lfs merge=lfs -text
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diff --git a/task/ai2_arc/README.md b/task/ai2_arc/README.md
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+---
+annotations_creators:
+- found
+language_creators:
+- found
+language:
+- en
+license:
+- cc-by-sa-4.0
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- question-answering
+task_ids:
+- open-domain-qa
+- multiple-choice-qa
+pretty_name: Ai2Arc
+language_bcp47:
+- en-US
+dataset_info:
+- config_name: ARC-Challenge
+  features:
+  - name: id
+    dtype: string
+  - name: question
+    dtype: string
+  - name: choices
+    sequence:
+    - name: text
+      dtype: string
+    - name: label
+      dtype: string
+  - name: answerKey
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 349760
+    num_examples: 1119
+  - name: test
+    num_bytes: 375511
+    num_examples: 1172
+  - name: validation
+    num_bytes: 96660
+    num_examples: 299
+  download_size: 449460
+  dataset_size: 821931
+- config_name: ARC-Easy
+  features:
+  - name: id
+    dtype: string
+  - name: question
+    dtype: string
+  - name: choices
+    sequence:
+    - name: text
+      dtype: string
+    - name: label
+      dtype: string
+  - name: answerKey
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 619000
+    num_examples: 2251
+  - name: test
+    num_bytes: 657514
+    num_examples: 2376
+  - name: validation
+    num_bytes: 157394
+    num_examples: 570
+  download_size: 762935
+  dataset_size: 1433908
+configs:
+- config_name: ARC-Challenge
+  data_files:
+  - split: train
+    path: ARC-Challenge/train-*
+  - split: test
+    path: ARC-Challenge/test-*
+  - split: validation
+    path: ARC-Challenge/validation-*
+- config_name: ARC-Easy
+  data_files:
+  - split: train
+    path: ARC-Easy/train-*
+  - split: test
+    path: ARC-Easy/test-*
+  - split: validation
+    path: ARC-Easy/validation-*
+---
+
+# Dataset Card for "ai2_arc"
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** [https://allenai.org/data/arc](https://allenai.org/data/arc)
+- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Paper:** [Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge](https://arxiv.org/abs/1803.05457)
+- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Size of downloaded dataset files:** 1361.68 MB
+- **Size of the generated dataset:** 2.28 MB
+- **Total amount of disk used:** 1363.96 MB
+
+### Dataset Summary
+
+A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in
+ advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains
+ only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also
+ including a corpus of over 14 million science sentences relevant to the task, and an implementation of three neural baseline models for this dataset. We pose ARC as a challenge to the community.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Languages
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## Dataset Structure
+
+### Data Instances
+
+#### ARC-Challenge
+
+- **Size of downloaded dataset files:** 680.84 MB
+- **Size of the generated dataset:** 0.83 MB
+- **Total amount of disk used:** 681.67 MB
+
+An example of 'train' looks as follows.
+```
+{
+    "answerKey": "B",
+    "choices": {
+        "label": ["A", "B", "C", "D"],
+        "text": ["Shady areas increased.", "Food sources increased.", "Oxygen levels increased.", "Available water increased."]
+    },
+    "id": "Mercury_SC_405487",
+    "question": "One year, the oak trees in a park began producing more acorns than usual. The next year, the population of chipmunks in the park also increased. Which best explains why there were more chipmunks the next year?"
+}
+```
+
+#### ARC-Easy
+
+- **Size of downloaded dataset files:** 680.84 MB
+- **Size of the generated dataset:** 1.45 MB
+- **Total amount of disk used:** 682.29 MB
+
+An example of 'train' looks as follows.
+```
+{
+    "answerKey": "B",
+    "choices": {
+        "label": ["A", "B", "C", "D"],
+        "text": ["Shady areas increased.", "Food sources increased.", "Oxygen levels increased.", "Available water increased."]
+    },
+    "id": "Mercury_SC_405487",
+    "question": "One year, the oak trees in a park began producing more acorns than usual. The next year, the population of chipmunks in the park also increased. Which best explains why there were more chipmunks the next year?"
+}
+```
+
+### Data Fields
+
+The data fields are the same among all splits.
+
+#### ARC-Challenge
+- `id`: a `string` feature.
+- `question`: a `string` feature.
+- `choices`: a dictionary feature containing:
+  - `text`: a `string` feature.
+  - `label`: a `string` feature.
+- `answerKey`: a `string` feature.
+
+#### ARC-Easy
+- `id`: a `string` feature.
+- `question`: a `string` feature.
+- `choices`: a dictionary feature containing:
+  - `text`: a `string` feature.
+  - `label`: a `string` feature.
+- `answerKey`: a `string` feature.
+
+### Data Splits
+
+|    name     |train|validation|test|
+|-------------|----:|---------:|---:|
+|ARC-Challenge| 1119|       299|1172|
+|ARC-Easy     | 2251|       570|2376|
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+#### Who are the source language producers?
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+#### Who are the annotators?
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Personal and Sensitive Information
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Discussion of Biases
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Other Known Limitations
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Licensing Information
+
+[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+
+### Citation Information
+
+```
+@article{allenai:arc,
+      author    = {Peter Clark  and Isaac Cowhey and Oren Etzioni and Tushar Khot and
+                    Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord},
+      title     = {Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge},
+      journal   = {arXiv:1803.05457v1},
+      year      = {2018},
+}
+
+```
+
+
+### Contributions
+
+Thanks to [@lewtun](https://github.com/lewtun), [@patrickvonplaten](https://github.com/patrickvonplaten), [@thomwolf](https://github.com/thomwolf) for adding this dataset.
\ No newline at end of file
diff --git a/task/gsm8k/.gitattributes b/task/gsm8k/.gitattributes
new file mode 100644
index 0000000000000000000000000000000000000000..227449ad6054efe1ce07c6aa12090bc57103f85f
--- /dev/null
+++ b/task/gsm8k/.gitattributes
@@ -0,0 +1,38 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
diff --git a/task/gsm8k/README.md b/task/gsm8k/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..ad25b2c451d0fcd2793678b2baa917c962acf281
--- /dev/null
+++ b/task/gsm8k/README.md
@@ -0,0 +1,226 @@
+---
+annotations_creators:
+- crowdsourced
+language_creators:
+- crowdsourced
+language:
+- en
+license:
+- mit
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- text-generation
+task_ids: []
+paperswithcode_id: gsm8k
+pretty_name: Grade School Math 8K
+tags:
+- math-word-problems
+dataset_info:
+- config_name: main
+  features:
+  - name: question
+    dtype: string
+  - name: answer
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 3963202
+    num_examples: 7473
+  - name: test
+    num_bytes: 713732
+    num_examples: 1319
+  download_size: 2725633
+  dataset_size: 4676934
+- config_name: socratic
+  features:
+  - name: question
+    dtype: string
+  - name: answer
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 5198108
+    num_examples: 7473
+  - name: test
+    num_bytes: 936859
+    num_examples: 1319
+  download_size: 3164254
+  dataset_size: 6134967
+configs:
+- config_name: main
+  data_files:
+  - split: train
+    path: main/train-*
+  - split: test
+    path: main/test-*
+- config_name: socratic
+  data_files:
+  - split: train
+    path: socratic/train-*
+  - split: test
+    path: socratic/test-*
+---
+
+# Dataset Card for GSM8K
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** https://openai.com/blog/grade-school-math/
+- **Repository:** https://github.com/openai/grade-school-math
+- **Paper:** https://arxiv.org/abs/2110.14168
+- **Leaderboard:** [Needs More Information]
+- **Point of Contact:** [Needs More Information]
+
+### Dataset Summary
+
+GSM8K (Grade School Math 8K) is a dataset of 8.5K high quality linguistically diverse grade school math word problems. The dataset was created to support the task of question answering on basic mathematical problems that require multi-step reasoning.
+- These problems take between 2 and 8 steps to solve.
+- Solutions primarily involve performing a sequence of elementary calculations using basic arithmetic operations (+ − ×÷) to reach the final answer.
+- A bright middle school student should be able to solve every problem: from the paper, "Problems require no concepts beyond the level of early Algebra, and the vast majority of problems can be solved without explicitly defining a variable."
+- Solutions are provided in natural language, as opposed to pure math expressions. From the paper: "We believe this is the most generally useful data format, and we expect it to shed light on the properties of large language models’ internal monologues""
+
+### Supported Tasks and Leaderboards
+
+This dataset is generally used to test logic and math in language modelling.
+It has been used for many benchmarks, including the [LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
+
+### Languages
+
+The text in the dataset is in English. The associated BCP-47 code is `en`.
+
+## Dataset Structure
+
+### Data Instances
+
+For the `main` configuration, each instance contains a string for the grade-school level math question and a string for the corresponding answer with multiple steps of reasoning and calculator annotations (explained [here](https://github.com/openai/grade-school-math#calculation-annotations)).
+
+
+```python
+{
+    'question': 'Natalia sold clips to 48 of her friends in April, and then she sold half as many clips in May. How many clips did Natalia sell altogether in April and May?',
+    'answer': 'Natalia sold 48/2 = <<48/2=24>>24 clips in May.\nNatalia sold 48+24 = <<48+24=72>>72 clips altogether in April and May.\n#### 72',
+}
+```
+
+For the `socratic` configuration, each instance contains a string for a grade-school level math question, a string for the corresponding answer with multiple steps of reasoning, calculator annotations (explained [here](https://github.com/openai/grade-school-math#calculation-annotations)), and *Socratic sub-questions*.
+
+```python
+{
+    'question': 'Natalia sold clips to 48 of her friends in April, and then she sold half as many clips in May. How many clips did Natalia sell altogether in April and May?',
+    'answer': 'How many clips did Natalia sell in May? ** Natalia sold 48/2 = <<48/2=24>>24 clips in May.\nHow many clips did Natalia sell altogether in April and May? ** Natalia sold 48+24 = <<48+24=72>>72 clips altogether in April and May.\n#### 72',
+}
+```
+
+### Data Fields
+
+The data fields are the same among `main` and `socratic` configurations and their individual splits.
+
+- question: The question string to a grade school math problem.
+
+- answer: The full solution string to the `question`. It contains multiple steps of reasoning with calculator annotations and the final numeric solution.
+
+### Data Splits
+
+| name   |train|validation|
+|--------|----:|---------:|
+|main    | 7473|      1319|
+|socratic| 7473|      1319|
+
+## Dataset Creation
+
+### Curation Rationale
+
+[Needs More Information]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+From the paper, appendix A:
+
+> We initially collected a starting set of a thousand problems and natural language solutions by hiring freelance contractors on Upwork (upwork.com). We then worked with Surge AI (surgehq.ai), an NLP data labeling platform, to scale up our data collection. After collecting the full dataset, we asked workers to re-solve all problems, with no workers re-solving problems they originally wrote. We checked whether their final answers agreed with the original solutions, and any problems that produced disagreements were either repaired or discarded. We then performed another round of agreement checks on a smaller subset of problems, finding that 1.7% of problems still produce disagreements among contractors. We estimate this to be the fraction of problems that contain breaking errors or ambiguities. It is possible that a larger percentage of problems contain subtle errors.
+
+#### Who are the source language producers?
+
+[Needs More Information]
+
+### Annotations
+
+#### Annotation process
+
+[Needs More Information]
+
+#### Who are the annotators?
+
+Surge AI (surgehq.ai)
+
+### Personal and Sensitive Information
+
+[Needs More Information]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[Needs More Information]
+
+### Discussion of Biases
+
+[Needs More Information]
+
+### Other Known Limitations
+
+[Needs More Information]
+
+## Additional Information
+
+### Dataset Curators
+
+[Needs More Information]
+
+### Licensing Information
+
+The GSM8K dataset is licensed under the [MIT License](https://opensource.org/licenses/MIT).
+
+### Citation Information
+
+```bibtex
+@article{cobbe2021gsm8k,
+  title={Training Verifiers to Solve Math Word Problems},
+  author={Cobbe, Karl and Kosaraju, Vineet and Bavarian, Mohammad and Chen, Mark and Jun, Heewoo and Kaiser, Lukasz and Plappert, Matthias and Tworek, Jerry and Hilton, Jacob and Nakano, Reiichiro and Hesse, Christopher and Schulman, John},
+  journal={arXiv preprint arXiv:2110.14168},
+  year={2021}
+}
+```
+
+### Contributions
+
+Thanks to [@jon-tow](https://github.com/jon-tow) for adding this dataset.
\ No newline at end of file
diff --git a/task/gsm8k/eval.yaml b/task/gsm8k/eval.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f3e73f8553be0ef91630ee4006fa0dfef00d3aee
--- /dev/null
+++ b/task/gsm8k/eval.yaml
@@ -0,0 +1,33 @@
+# yaml file for compatibility with inspect-ai
+
+name: GSM8K
+description: >
+  GSM8K is a dataset of 8,000+ high-quality, single-step arithmetic word problems.
+
+tasks:
+  - id: gsm8k
+    config: main
+    split: test
+
+    epochs: 4
+    epoch_reducer: pass_at_1
+
+    field_spec:
+      input: question
+      target: answer
+
+    solvers:
+      - name: prompt_template
+        args:
+          template: >
+            Solve the following math problem efficiently and clearly.  The last line
+            of your response should be of the following format: 'Therefore, the final
+            answer is: $\\boxed{ANSWER}$. I hope it is correct' (without quotes)
+            where ANSWER is just the final number or expression that solves the
+            problem. Think step by step before answering.
+
+            {prompt}
+      - name: generate
+          
+    scorers:
+      - name: model_graded_fact
diff --git a/task/gsm8k/main/test-00000-of-00001.parquet b/task/gsm8k/main/test-00000-of-00001.parquet
new file mode 100644
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--- /dev/null
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ee7b8da9e381df27b9e3f7758a159ab2bdaa4dbaa910546cbbc47e0cb44e4f59
+size 419088
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new file mode 100644
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+oid sha256:ea82612ea9582142387730c793eb67d3b12849002bc0b7fa6f8efafa7351419d
+size 2306545
diff --git a/task/gsm8k/socratic/test-00000-of-00001.parquet b/task/gsm8k/socratic/test-00000-of-00001.parquet
new file mode 100644
index 0000000000000000000000000000000000000000..a3283da59daba24a5a4b4e580535f0195abd313e
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@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:477dba7028204b465491b8f346ec774262ccd77147d942a0881e94cc6da7c99e
+size 486995
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new file mode 100644
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+oid sha256:54eb5fd2105a9126ac6410541b2e9dbe0199701258957c9af02d9ed675c90378
+size 2677259
diff --git a/task/humaneval/.gitattributes b/task/humaneval/.gitattributes
new file mode 100644
index 0000000000000000000000000000000000000000..957b2579c6ef20995a09efd9a17f8fd90606f5ed
--- /dev/null
+++ b/task/humaneval/.gitattributes
@@ -0,0 +1,27 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
diff --git a/task/humaneval/README.md b/task/humaneval/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..09b3df651a754ebd00f7585289da42c9b90862de
--- /dev/null
+++ b/task/humaneval/README.md
@@ -0,0 +1,208 @@
+---
+annotations_creators:
+- expert-generated
+language_creators:
+- expert-generated
+language:
+- en
+license:
+- mit
+multilinguality:
+- monolingual
+size_categories:
+- n<1K
+source_datasets:
+- original
+task_categories:
+- text2text-generation
+task_ids: []
+paperswithcode_id: humaneval
+pretty_name: OpenAI HumanEval
+tags:
+- code-generation
+dataset_info:
+  config_name: openai_humaneval
+  features:
+  - name: task_id
+    dtype: string
+  - name: prompt
+    dtype: string
+  - name: canonical_solution
+    dtype: string
+  - name: test
+    dtype: string
+  - name: entry_point
+    dtype: string
+  splits:
+  - name: test
+    num_bytes: 194394
+    num_examples: 164
+  download_size: 83920
+  dataset_size: 194394
+configs:
+- config_name: openai_humaneval
+  data_files:
+  - split: test
+    path: openai_humaneval/test-*
+  default: true
+---
+
+# Dataset Card for OpenAI HumanEval
+
+## Table of Contents
+- [OpenAI HumanEval](#openai-humaneval)
+  - [Table of Contents](#table-of-contents)
+  - [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+  - [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+  - [Dataset Creation](#dataset-creation)
+    - [Curation Rationale](#curation-rationale)
+    - [Source Data](#source-data)
+      - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
+      - [Who are the source language producers?](#who-are-the-source-language-producers)
+    - [Annotations](#annotations)
+      - [Annotation process](#annotation-process)
+      - [Who are the annotators?](#who-are-the-annotators)
+    - [Personal and Sensitive Information](#personal-and-sensitive-information)
+  - [Considerations for Using the Data](#considerations-for-using-the-data)
+    - [Social Impact of Dataset](#social-impact-of-dataset)
+    - [Discussion of Biases](#discussion-of-biases)
+    - [Other Known Limitations](#other-known-limitations)
+  - [Additional Information](#additional-information)
+    - [Dataset Curators](#dataset-curators)
+    - [Licensing Information](#licensing-information)
+    - [Citation Information](#citation-information)
+    - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Repository:** [GitHub Repository](https://github.com/openai/human-eval)
+- **Paper:** [Evaluating Large Language Models Trained on Code](https://arxiv.org/abs/2107.03374)
+
+### Dataset Summary
+
+The HumanEval dataset released by OpenAI includes 164 programming problems with a function sig- nature, docstring, body, and several unit tests. They were handwritten to ensure not to be included in the training set of code generation models.
+
+### Supported Tasks and Leaderboards
+
+### Languages
+The programming problems are written in Python and contain English natural text in comments and docstrings.
+
+## Dataset Structure
+
+```python
+from datasets import load_dataset
+load_dataset("openai_humaneval")
+
+DatasetDict({
+    test: Dataset({
+        features: ['task_id', 'prompt', 'canonical_solution', 'test', 'entry_point'],
+        num_rows: 164
+    })
+})
+```
+
+### Data Instances
+
+An example of a dataset instance:
+
+```
+{
+    "task_id": "test/0",
+    "prompt": "def return1():\n",
+    "canonical_solution": "    return 1",
+    "test": "def check(candidate):\n    assert candidate() == 1",
+    "entry_point": "return1"
+}
+```
+
+### Data Fields
+
+- `task_id`: identifier for the data sample
+- `prompt`: input for the model containing function header and docstrings
+- `canonical_solution`: solution for the problem in the `prompt`
+- `test`: contains function to test generated code for correctness
+- `entry_point`: entry point for test
+
+
+### Data Splits
+
+The dataset only consists of a test split with 164 samples.
+
+## Dataset Creation
+
+### Curation Rationale
+
+Since code generation models are often trained on dumps of GitHub a dataset not included in the dump was necessary to properly evaluate the model. However, since this dataset was published on GitHub it is likely to be included in future dumps.
+
+### Source Data
+
+The dataset was handcrafted by engineers and researchers at OpenAI.
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+[More Information Needed]
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+None.
+
+## Considerations for Using the Data
+Make sure you execute generated Python code in a safe environment when evauating against this dataset as generated code could be harmful.
+
+### Social Impact of Dataset
+With this dataset code generating models can be better evaluated which leads to fewer issues introduced when using such models.
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+OpenAI
+
+### Licensing Information
+
+MIT License
+
+### Citation Information
+```
+@misc{chen2021evaluating,
+      title={Evaluating Large Language Models Trained on Code},
+      author={Mark Chen and Jerry Tworek and Heewoo Jun and Qiming Yuan and Henrique Ponde de Oliveira Pinto and Jared Kaplan and Harri Edwards and Yuri Burda and Nicholas Joseph and Greg Brockman and Alex Ray and Raul Puri and Gretchen Krueger and Michael Petrov and Heidy Khlaaf and Girish Sastry and Pamela Mishkin and Brooke Chan and Scott Gray and Nick Ryder and Mikhail Pavlov and Alethea Power and Lukasz Kaiser and Mohammad Bavarian and Clemens Winter and Philippe Tillet and Felipe Petroski Such and Dave Cummings and Matthias Plappert and Fotios Chantzis and Elizabeth Barnes and Ariel Herbert-Voss and William Hebgen Guss and Alex Nichol and Alex Paino and Nikolas Tezak and Jie Tang and Igor Babuschkin and Suchir Balaji and Shantanu Jain and William Saunders and Christopher Hesse and Andrew N. Carr and Jan Leike and Josh Achiam and Vedant Misra and Evan Morikawa and Alec Radford and Matthew Knight and Miles Brundage and Mira Murati and Katie Mayer and Peter Welinder and Bob McGrew and Dario Amodei and Sam McCandlish and Ilya Sutskever and Wojciech Zaremba},
+      year={2021},
+      eprint={2107.03374},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG}
+}
+```
+
+### Contributions
+
+Thanks to [@lvwerra](https://github.com/lvwerra) for adding this dataset.
\ No newline at end of file
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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*.ckpt filter=lfs diff=lfs merge=lfs -text
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+*.lfs.* filter=lfs diff=lfs merge=lfs -text
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+*.pkl filter=lfs diff=lfs merge=lfs -text
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+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
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+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
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+# Audio files - compressed
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+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
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+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
diff --git a/task/mmlu/README.md b/task/mmlu/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..08de94c560ad7420252bff6e4729f1d1683def4f
--- /dev/null
+++ b/task/mmlu/README.md
@@ -0,0 +1,2299 @@
+---
+annotations_creators:
+- no-annotation
+language_creators:
+- expert-generated
+language:
+- en
+license:
+- mit
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- question-answering
+task_ids:
+- multiple-choice-qa
+paperswithcode_id: mmlu
+pretty_name: Measuring Massive Multitask Language Understanding
+language_bcp47:
+- en-US
+dataset_info:
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+- config_name: anatomy
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+- config_name: econometrics
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+- config_name: elementary_mathematics
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+- config_name: high_school_european_history
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+- config_name: high_school_government_and_politics
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+- config_name: high_school_macroeconomics
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+- config_name: high_school_physics
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+- config_name: high_school_world_history
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+- config_name: human_sexuality
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+- config_name: international_law
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+- config_name: jurisprudence
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+- config_name: machine_learning
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+  - name: question
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+  - name: subject
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+- config_name: management
+  features:
+  - name: question
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+- config_name: marketing
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+- config_name: medical_genetics
+  features:
+  - name: question
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+- config_name: miscellaneous
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+- config_name: moral_disputes
+  features:
+  - name: question
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+  - name: subject
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+- config_name: moral_scenarios
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+  - name: question
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+- config_name: nutrition
+  features:
+  - name: question
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+- config_name: philosophy
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+- config_name: prehistory
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+- config_name: professional_accounting
+  features:
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+- config_name: professional_law
+  features:
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+- config_name: professional_medicine
+  features:
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+- config_name: professional_psychology
+  features:
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+- config_name: public_relations
+  features:
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+- config_name: security_studies
+  features:
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+  - name: subject
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+- config_name: sociology
+  features:
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+- config_name: us_foreign_policy
+  features:
+  - name: question
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+  - name: subject
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+  - name: choices
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+- config_name: virology
+  features:
+  - name: question
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+  - name: subject
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+- config_name: world_religions
+  features:
+  - name: question
+    dtype: string
+  - name: subject
+    dtype: string
+  - name: choices
+    sequence: string
+  - name: answer
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+    num_examples: 5
+  download_size: 27165
+  dataset_size: 96522.07438591801
+configs:
+- config_name: abstract_algebra
+  data_files:
+  - split: test
+    path: abstract_algebra/test-*
+  - split: validation
+    path: abstract_algebra/validation-*
+  - split: dev
+    path: abstract_algebra/dev-*
+- config_name: all
+  data_files:
+  - split: test
+    path: all/test-*
+  - split: validation
+    path: all/validation-*
+  - split: dev
+    path: all/dev-*
+  - split: auxiliary_train
+    path: all/auxiliary_train-*
+- config_name: anatomy
+  data_files:
+  - split: test
+    path: anatomy/test-*
+  - split: validation
+    path: anatomy/validation-*
+  - split: dev
+    path: anatomy/dev-*
+- config_name: astronomy
+  data_files:
+  - split: test
+    path: astronomy/test-*
+  - split: validation
+    path: astronomy/validation-*
+  - split: dev
+    path: astronomy/dev-*
+- config_name: auxiliary_train
+  data_files:
+  - split: train
+    path: auxiliary_train/train-*
+- config_name: business_ethics
+  data_files:
+  - split: test
+    path: business_ethics/test-*
+  - split: validation
+    path: business_ethics/validation-*
+  - split: dev
+    path: business_ethics/dev-*
+- config_name: clinical_knowledge
+  data_files:
+  - split: test
+    path: clinical_knowledge/test-*
+  - split: validation
+    path: clinical_knowledge/validation-*
+  - split: dev
+    path: clinical_knowledge/dev-*
+- config_name: college_biology
+  data_files:
+  - split: test
+    path: college_biology/test-*
+  - split: validation
+    path: college_biology/validation-*
+  - split: dev
+    path: college_biology/dev-*
+- config_name: college_chemistry
+  data_files:
+  - split: test
+    path: college_chemistry/test-*
+  - split: validation
+    path: college_chemistry/validation-*
+  - split: dev
+    path: college_chemistry/dev-*
+- config_name: college_computer_science
+  data_files:
+  - split: test
+    path: college_computer_science/test-*
+  - split: validation
+    path: college_computer_science/validation-*
+  - split: dev
+    path: college_computer_science/dev-*
+- config_name: college_mathematics
+  data_files:
+  - split: test
+    path: college_mathematics/test-*
+  - split: validation
+    path: college_mathematics/validation-*
+  - split: dev
+    path: college_mathematics/dev-*
+- config_name: college_medicine
+  data_files:
+  - split: test
+    path: college_medicine/test-*
+  - split: validation
+    path: college_medicine/validation-*
+  - split: dev
+    path: college_medicine/dev-*
+- config_name: college_physics
+  data_files:
+  - split: test
+    path: college_physics/test-*
+  - split: validation
+    path: college_physics/validation-*
+  - split: dev
+    path: college_physics/dev-*
+- config_name: computer_security
+  data_files:
+  - split: test
+    path: computer_security/test-*
+  - split: validation
+    path: computer_security/validation-*
+  - split: dev
+    path: computer_security/dev-*
+- config_name: conceptual_physics
+  data_files:
+  - split: test
+    path: conceptual_physics/test-*
+  - split: validation
+    path: conceptual_physics/validation-*
+  - split: dev
+    path: conceptual_physics/dev-*
+- config_name: econometrics
+  data_files:
+  - split: test
+    path: econometrics/test-*
+  - split: validation
+    path: econometrics/validation-*
+  - split: dev
+    path: econometrics/dev-*
+- config_name: electrical_engineering
+  data_files:
+  - split: test
+    path: electrical_engineering/test-*
+  - split: validation
+    path: electrical_engineering/validation-*
+  - split: dev
+    path: electrical_engineering/dev-*
+- config_name: elementary_mathematics
+  data_files:
+  - split: test
+    path: elementary_mathematics/test-*
+  - split: validation
+    path: elementary_mathematics/validation-*
+  - split: dev
+    path: elementary_mathematics/dev-*
+- config_name: formal_logic
+  data_files:
+  - split: test
+    path: formal_logic/test-*
+  - split: validation
+    path: formal_logic/validation-*
+  - split: dev
+    path: formal_logic/dev-*
+- config_name: global_facts
+  data_files:
+  - split: test
+    path: global_facts/test-*
+  - split: validation
+    path: global_facts/validation-*
+  - split: dev
+    path: global_facts/dev-*
+- config_name: high_school_biology
+  data_files:
+  - split: test
+    path: high_school_biology/test-*
+  - split: validation
+    path: high_school_biology/validation-*
+  - split: dev
+    path: high_school_biology/dev-*
+- config_name: high_school_chemistry
+  data_files:
+  - split: test
+    path: high_school_chemistry/test-*
+  - split: validation
+    path: high_school_chemistry/validation-*
+  - split: dev
+    path: high_school_chemistry/dev-*
+- config_name: high_school_computer_science
+  data_files:
+  - split: test
+    path: high_school_computer_science/test-*
+  - split: validation
+    path: high_school_computer_science/validation-*
+  - split: dev
+    path: high_school_computer_science/dev-*
+- config_name: high_school_european_history
+  data_files:
+  - split: test
+    path: high_school_european_history/test-*
+  - split: validation
+    path: high_school_european_history/validation-*
+  - split: dev
+    path: high_school_european_history/dev-*
+- config_name: high_school_geography
+  data_files:
+  - split: test
+    path: high_school_geography/test-*
+  - split: validation
+    path: high_school_geography/validation-*
+  - split: dev
+    path: high_school_geography/dev-*
+- config_name: high_school_government_and_politics
+  data_files:
+  - split: test
+    path: high_school_government_and_politics/test-*
+  - split: validation
+    path: high_school_government_and_politics/validation-*
+  - split: dev
+    path: high_school_government_and_politics/dev-*
+- config_name: high_school_macroeconomics
+  data_files:
+  - split: test
+    path: high_school_macroeconomics/test-*
+  - split: validation
+    path: high_school_macroeconomics/validation-*
+  - split: dev
+    path: high_school_macroeconomics/dev-*
+- config_name: high_school_mathematics
+  data_files:
+  - split: test
+    path: high_school_mathematics/test-*
+  - split: validation
+    path: high_school_mathematics/validation-*
+  - split: dev
+    path: high_school_mathematics/dev-*
+- config_name: high_school_microeconomics
+  data_files:
+  - split: test
+    path: high_school_microeconomics/test-*
+  - split: validation
+    path: high_school_microeconomics/validation-*
+  - split: dev
+    path: high_school_microeconomics/dev-*
+- config_name: high_school_physics
+  data_files:
+  - split: test
+    path: high_school_physics/test-*
+  - split: validation
+    path: high_school_physics/validation-*
+  - split: dev
+    path: high_school_physics/dev-*
+- config_name: high_school_psychology
+  data_files:
+  - split: test
+    path: high_school_psychology/test-*
+  - split: validation
+    path: high_school_psychology/validation-*
+  - split: dev
+    path: high_school_psychology/dev-*
+- config_name: high_school_statistics
+  data_files:
+  - split: test
+    path: high_school_statistics/test-*
+  - split: validation
+    path: high_school_statistics/validation-*
+  - split: dev
+    path: high_school_statistics/dev-*
+- config_name: high_school_us_history
+  data_files:
+  - split: test
+    path: high_school_us_history/test-*
+  - split: validation
+    path: high_school_us_history/validation-*
+  - split: dev
+    path: high_school_us_history/dev-*
+- config_name: high_school_world_history
+  data_files:
+  - split: test
+    path: high_school_world_history/test-*
+  - split: validation
+    path: high_school_world_history/validation-*
+  - split: dev
+    path: high_school_world_history/dev-*
+- config_name: human_aging
+  data_files:
+  - split: test
+    path: human_aging/test-*
+  - split: validation
+    path: human_aging/validation-*
+  - split: dev
+    path: human_aging/dev-*
+- config_name: human_sexuality
+  data_files:
+  - split: test
+    path: human_sexuality/test-*
+  - split: validation
+    path: human_sexuality/validation-*
+  - split: dev
+    path: human_sexuality/dev-*
+- config_name: international_law
+  data_files:
+  - split: test
+    path: international_law/test-*
+  - split: validation
+    path: international_law/validation-*
+  - split: dev
+    path: international_law/dev-*
+- config_name: jurisprudence
+  data_files:
+  - split: test
+    path: jurisprudence/test-*
+  - split: validation
+    path: jurisprudence/validation-*
+  - split: dev
+    path: jurisprudence/dev-*
+- config_name: logical_fallacies
+  data_files:
+  - split: test
+    path: logical_fallacies/test-*
+  - split: validation
+    path: logical_fallacies/validation-*
+  - split: dev
+    path: logical_fallacies/dev-*
+- config_name: machine_learning
+  data_files:
+  - split: test
+    path: machine_learning/test-*
+  - split: validation
+    path: machine_learning/validation-*
+  - split: dev
+    path: machine_learning/dev-*
+- config_name: management
+  data_files:
+  - split: test
+    path: management/test-*
+  - split: validation
+    path: management/validation-*
+  - split: dev
+    path: management/dev-*
+- config_name: marketing
+  data_files:
+  - split: test
+    path: marketing/test-*
+  - split: validation
+    path: marketing/validation-*
+  - split: dev
+    path: marketing/dev-*
+- config_name: medical_genetics
+  data_files:
+  - split: test
+    path: medical_genetics/test-*
+  - split: validation
+    path: medical_genetics/validation-*
+  - split: dev
+    path: medical_genetics/dev-*
+- config_name: miscellaneous
+  data_files:
+  - split: test
+    path: miscellaneous/test-*
+  - split: validation
+    path: miscellaneous/validation-*
+  - split: dev
+    path: miscellaneous/dev-*
+- config_name: moral_disputes
+  data_files:
+  - split: test
+    path: moral_disputes/test-*
+  - split: validation
+    path: moral_disputes/validation-*
+  - split: dev
+    path: moral_disputes/dev-*
+- config_name: moral_scenarios
+  data_files:
+  - split: test
+    path: moral_scenarios/test-*
+  - split: validation
+    path: moral_scenarios/validation-*
+  - split: dev
+    path: moral_scenarios/dev-*
+- config_name: nutrition
+  data_files:
+  - split: test
+    path: nutrition/test-*
+  - split: validation
+    path: nutrition/validation-*
+  - split: dev
+    path: nutrition/dev-*
+- config_name: philosophy
+  data_files:
+  - split: test
+    path: philosophy/test-*
+  - split: validation
+    path: philosophy/validation-*
+  - split: dev
+    path: philosophy/dev-*
+- config_name: prehistory
+  data_files:
+  - split: test
+    path: prehistory/test-*
+  - split: validation
+    path: prehistory/validation-*
+  - split: dev
+    path: prehistory/dev-*
+- config_name: professional_accounting
+  data_files:
+  - split: test
+    path: professional_accounting/test-*
+  - split: validation
+    path: professional_accounting/validation-*
+  - split: dev
+    path: professional_accounting/dev-*
+- config_name: professional_law
+  data_files:
+  - split: test
+    path: professional_law/test-*
+  - split: validation
+    path: professional_law/validation-*
+  - split: dev
+    path: professional_law/dev-*
+- config_name: professional_medicine
+  data_files:
+  - split: test
+    path: professional_medicine/test-*
+  - split: validation
+    path: professional_medicine/validation-*
+  - split: dev
+    path: professional_medicine/dev-*
+- config_name: professional_psychology
+  data_files:
+  - split: test
+    path: professional_psychology/test-*
+  - split: validation
+    path: professional_psychology/validation-*
+  - split: dev
+    path: professional_psychology/dev-*
+- config_name: public_relations
+  data_files:
+  - split: test
+    path: public_relations/test-*
+  - split: validation
+    path: public_relations/validation-*
+  - split: dev
+    path: public_relations/dev-*
+- config_name: security_studies
+  data_files:
+  - split: test
+    path: security_studies/test-*
+  - split: validation
+    path: security_studies/validation-*
+  - split: dev
+    path: security_studies/dev-*
+- config_name: sociology
+  data_files:
+  - split: test
+    path: sociology/test-*
+  - split: validation
+    path: sociology/validation-*
+  - split: dev
+    path: sociology/dev-*
+- config_name: us_foreign_policy
+  data_files:
+  - split: test
+    path: us_foreign_policy/test-*
+  - split: validation
+    path: us_foreign_policy/validation-*
+  - split: dev
+    path: us_foreign_policy/dev-*
+- config_name: virology
+  data_files:
+  - split: test
+    path: virology/test-*
+  - split: validation
+    path: virology/validation-*
+  - split: dev
+    path: virology/dev-*
+- config_name: world_religions
+  data_files:
+  - split: test
+    path: world_religions/test-*
+  - split: validation
+    path: world_religions/validation-*
+  - split: dev
+    path: world_religions/dev-*
+---
+
+# Dataset Card for MMLU
+
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Repository**: https://github.com/hendrycks/test
+- **Paper**: https://arxiv.org/abs/2009.03300
+
+### Dataset Summary
+
+[Measuring Massive Multitask Language Understanding](https://arxiv.org/pdf/2009.03300) by [Dan Hendrycks](https://people.eecs.berkeley.edu/~hendrycks/), [Collin Burns](http://collinpburns.com), [Steven Basart](https://stevenbas.art), Andy Zou, Mantas Mazeika, [Dawn Song](https://people.eecs.berkeley.edu/~dawnsong/), and [Jacob Steinhardt](https://www.stat.berkeley.edu/~jsteinhardt/) (ICLR 2021).
+
+This is a massive multitask test consisting of multiple-choice questions from various branches of knowledge. The test spans subjects in the humanities, social sciences, hard sciences, and other areas that are important for some people to learn. This covers 57 tasks including elementary mathematics, US history, computer science, law, and more. To attain high accuracy on this test, models must possess extensive world knowledge and problem solving ability.
+
+A complete list of tasks: ['abstract_algebra', 'anatomy', 'astronomy', 'business_ethics', 'clinical_knowledge', 'college_biology', 'college_chemistry', 'college_computer_science', 'college_mathematics', 'college_medicine', 'college_physics', 'computer_security', 'conceptual_physics', 'econometrics', 'electrical_engineering', 'elementary_mathematics', 'formal_logic', 'global_facts', 'high_school_biology', 'high_school_chemistry', 'high_school_computer_science', 'high_school_european_history', 'high_school_geography', 'high_school_government_and_politics', 'high_school_macroeconomics', 'high_school_mathematics', 'high_school_microeconomics', 'high_school_physics', 'high_school_psychology', 'high_school_statistics', 'high_school_us_history', 'high_school_world_history', 'human_aging', 'human_sexuality', 'international_law', 'jurisprudence', 'logical_fallacies', 'machine_learning', 'management', 'marketing', 'medical_genetics', 'miscellaneous', 'moral_disputes', 'moral_scenarios', 'nutrition', 'philosophy', 'prehistory', 'professional_accounting', 'professional_law', 'professional_medicine', 'professional_psychology', 'public_relations', 'security_studies', 'sociology', 'us_foreign_policy', 'virology', 'world_religions']
+
+### Supported Tasks and Leaderboards
+
+|                Model               | Authors |  Humanities |  Social Science  | STEM | Other | Average |
+|------------------------------------|----------|:-------:|:-------:|:-------:|:-------:|:-------:|
+| [UnifiedQA](https://arxiv.org/abs/2005.00700) | Khashabi et al., 2020 | 45.6 | 56.6 | 40.2 | 54.6 | 48.9
+| [GPT-3](https://arxiv.org/abs/2005.14165) (few-shot) | Brown et al., 2020 | 40.8 | 50.4 | 36.7 | 48.8 | 43.9
+| [GPT-2](https://arxiv.org/abs/2005.14165) | Radford et al., 2019 | 32.8 | 33.3 | 30.2 | 33.1 | 32.4
+| Random Baseline           | N/A | 25.0 | 25.0 | 25.0 | 25.0 | 25.0 | 25.0
+
+### Languages
+
+English
+
+## Dataset Structure
+
+### Data Instances
+
+An example from anatomy subtask looks as follows:
+```
+{
+  "question": "What is the embryological origin of the hyoid bone?",
+  "choices": ["The first pharyngeal arch", "The first and second pharyngeal arches", "The second pharyngeal arch", "The second and third pharyngeal arches"],
+  "answer": "D"
+}
+```
+
+### Data Fields
+
+- `question`: a string feature
+- `choices`: a list of 4 string features
+- `answer`: a ClassLabel feature
+
+### Data Splits
+
+- `auxiliary_train`: auxiliary multiple-choice training questions from ARC, MC_TEST, OBQA, RACE, etc.
+- `dev`: 5 examples per subtask, meant for few-shot setting
+- `test`: there are at least 100 examples per subtask
+
+|       | auxiliary_train   | dev | val | test |
+| ----- | :------: | :-----: | :-----: | :-----: |
+| TOTAL | 99842 | 285 | 1531 | 14042
+
+## Dataset Creation
+
+### Curation Rationale
+
+Transformer models have driven this recent progress by pretraining on massive text corpora, including all of Wikipedia, thousands of books, and numerous websites. These models consequently see extensive information about specialized topics, most of which is not assessed by existing NLP benchmarks. To bridge the gap between the wide-ranging knowledge that models see during pretraining and the existing measures of success, we introduce a new benchmark for assessing models across a diverse set of subjects that humans learn.
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[MIT License](https://github.com/hendrycks/test/blob/master/LICENSE)
+
+### Citation Information
+
+If you find this useful in your research, please consider citing the test and also the [ETHICS](https://arxiv.org/abs/2008.02275) dataset it draws from:
+```
+    @article{hendryckstest2021,
+      title={Measuring Massive Multitask Language Understanding},
+      author={Dan Hendrycks and Collin Burns and Steven Basart and Andy Zou and Mantas Mazeika and Dawn Song and Jacob Steinhardt},
+      journal={Proceedings of the International Conference on Learning Representations (ICLR)},
+      year={2021}
+    }
+
+    @article{hendrycks2021ethics,
+      title={Aligning AI With Shared Human Values},
+      author={Dan Hendrycks and Collin Burns and Steven Basart and Andrew Critch and Jerry Li and Dawn Song and Jacob Steinhardt},
+      journal={Proceedings of the International Conference on Learning Representations (ICLR)},
+      year={2021}
+    }
+```
+### Contributions
+
+Thanks to [@andyzoujm](https://github.com/andyzoujm) for adding this dataset.
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diff --git a/task/mmlu/hendrycks_test.py b/task/mmlu/hendrycks_test.py
new file mode 100644
index 0000000000000000000000000000000000000000..dbc9739b9e15d692ab2cc749c1d650df087b5ba4
--- /dev/null
+++ b/task/mmlu/hendrycks_test.py
@@ -0,0 +1,170 @@
+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+# this file is here for backward compatibility (e.g. for lm-evaluation-harness), when this dataset used to be named "hendrycks_test"
+
+import csv
+
+import datasets
+
+
+_CITATION = """\
+@article{hendryckstest2021,
+      title={Measuring Massive Multitask Language Understanding},
+      author={Dan Hendrycks and Collin Burns and Steven Basart and Andy Zou and Mantas Mazeika and Dawn Song and Jacob Steinhardt},
+      journal={Proceedings of the International Conference on Learning Representations (ICLR)},
+      year={2021}
+    }
+"""
+
+_DESCRIPTION = """\
+This is a massive multitask test consisting of multiple-choice questions from various branches of knowledge, covering 57 tasks including elementary mathematics, US history, computer science, law, and more.
+"""
+
+_HOMEPAGE = "https://github.com/hendrycks/test"
+
+_URL = "data.tar"
+
+_SUBJECTS = [
+    "abstract_algebra",
+    "anatomy",
+    "astronomy",
+    "business_ethics",
+    "clinical_knowledge",
+    "college_biology",
+    "college_chemistry",
+    "college_computer_science",
+    "college_mathematics",
+    "college_medicine",
+    "college_physics",
+    "computer_security",
+    "conceptual_physics",
+    "econometrics",
+    "electrical_engineering",
+    "elementary_mathematics",
+    "formal_logic",
+    "global_facts",
+    "high_school_biology",
+    "high_school_chemistry",
+    "high_school_computer_science",
+    "high_school_european_history",
+    "high_school_geography",
+    "high_school_government_and_politics",
+    "high_school_macroeconomics",
+    "high_school_mathematics",
+    "high_school_microeconomics",
+    "high_school_physics",
+    "high_school_psychology",
+    "high_school_statistics",
+    "high_school_us_history",
+    "high_school_world_history",
+    "human_aging",
+    "human_sexuality",
+    "international_law",
+    "jurisprudence",
+    "logical_fallacies",
+    "machine_learning",
+    "management",
+    "marketing",
+    "medical_genetics",
+    "miscellaneous",
+    "moral_disputes",
+    "moral_scenarios",
+    "nutrition",
+    "philosophy",
+    "prehistory",
+    "professional_accounting",
+    "professional_law",
+    "professional_medicine",
+    "professional_psychology",
+    "public_relations",
+    "security_studies",
+    "sociology",
+    "us_foreign_policy",
+    "virology",
+    "world_religions",
+]
+
+
+class HendrycksTest(datasets.GeneratorBasedBuilder):
+    """Massive multitask MC test cosisting of 57 tasks"""
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name=sub, version=datasets.Version("1.0.0"), description=f"Hendrycks Test Subject {sub}"
+        )
+        for sub in _SUBJECTS
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "question": datasets.Value("string"),
+                "choices": datasets.features.Sequence(datasets.Value("string")),
+                "answer": datasets.features.ClassLabel(num_classes=4, names=["A", "B", "C", "D"]),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        archive = dl_manager.download(_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split("auxiliary_train"),
+                gen_kwargs={
+                    "iter_archive": dl_manager.iter_archive(archive),
+                    "split": "auxiliary_train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"iter_archive": dl_manager.iter_archive(archive), "split": "test"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "iter_archive": dl_manager.iter_archive(archive),
+                    "split": "val",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split("dev"),
+                gen_kwargs={
+                    "iter_archive": dl_manager.iter_archive(archive),
+                    "split": "dev",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, iter_archive, split):
+        """Yields examples as (key, example) tuples."""
+        n_yielded_files = 0
+        for id_file, (path, file) in enumerate(iter_archive):
+            if f"data/{split}/" in path:
+                if split == "auxiliary_train" or f"{self.config.name}_{split}.csv" in path:
+                    n_yielded_files += 1
+                    lines = (line.decode("utf-8") for line in file)
+                    reader = csv.reader(lines)
+                    for id_line, data in enumerate(reader):
+                        yield f"{id_file}_{id_line}", {"question": data[0], "choices": data[1:5], "answer": data[5]}
+                    if n_yielded_files == 8 or split != "auxiliary_train":
+                        break
\ No newline at end of file
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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
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+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
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+*.aac filter=lfs diff=lfs merge=lfs -text
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diff --git a/task/smol-smoltalk/README.md b/task/smol-smoltalk/README.md
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+---
+license: apache-2.0
+language:
+- en
+tags:
+- synthetic
+pretty_name: Smol-SmolTalk
+size_categories:
+- 100K<n<1M
+dataset_info:
+  features:
+  - name: messages
+    list:
+    - name: content
+      dtype: string
+    - name: role
+      dtype: string
+  - name: source
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 1811694118.6259818
+    num_examples: 460341
+  - name: test
+    num_bytes: 95354393.3740182
+    num_examples: 24229
+  download_size: 970652749
+  dataset_size: 1907048512.0
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: test
+    path: data/test-*
+---
+
+# Smol-SmalTalk
+
+This is a subset of [SmolTalk](https://huggingface.co/datasets/HuggingFaceTB/smoltalk/) dataset adapted for smol models with less than 1B parameters. We used it to build [SmolLM2-360M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-360M-Instruct) and 
+[SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct/). We do SFT on this dataset and then DPO on UltraFeedback.
+
+Compared to SmolTalk: 
+- The conversations from Smol-Magpie-Ultra are shorter in this dataset
+- We include less task specific data compared to SmolTalk (e.g no function calling and less rewriting and summarization examples) since these smaller models have limited capacity
+- We don't include any advanced math datasets
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("HuggingFaceTB/smol-smoltalk", split="train")
+```
+
+## Citation
+```bash
+@misc{allal2025smollm2smolgoesbig,
+      title={SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model}, 
+      author={Loubna Ben Allal and Anton Lozhkov and Elie Bakouch and Gabriel Martín Blázquez and Guilherme Penedo and Lewis Tunstall and Andrés Marafioti and Hynek Kydlíček and Agustín Piqueres Lajarín and Vaibhav Srivastav and Joshua Lochner and Caleb Fahlgren and Xuan-Son Nguyen and Clémentine Fourrier and Ben Burtenshaw and Hugo Larcher and Haojun Zhao and Cyril Zakka and Mathieu Morlon and Colin Raffel and Leandro von Werra and Thomas Wolf},
+      year={2025},
+      eprint={2502.02737},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2502.02737}, 
+}
+```
\ No newline at end of file
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