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All datasets matching “task”OpenMLE-Tasks
OpenMLE Tasks
📄 Paper
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🌐 Project
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💻 Code
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🤗 Models
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📚 SFT Traces
OpenMLE Tasks provides machine-learning Task environments. The public SFT trajectories are released separately in OpenMLE-SFT-Traces. These resources accompany the paper Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering and the OpenRSI code release.
Release form
What is included… See the full description on the dataset page: https://huggingface.co/datasets/FrontisAI/OpenMLE-Tasks.mmluMMLU (hendrycks_test on huggingface) without auxiliary train. It is much lighter (7MB vs 162MB) and faster than the original implementation, in which auxiliary train is loaded (+ duplicated!) by default for all the configs in the original version, making it quite heavy.
We use this version in tasksource.
Reference to original dataset:
Measuring Massive Multitask Language Understanding - https://github.com/hendrycks/test
@article{hendryckstest2021,
title={Measuring Massive Multitask Language… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/mmlu.tasksThis dataset is for storing assets for https://huggingface.co/tasks and https://github.com/huggingface/huggingface.js/tree/main/packages/tasks
reclorhttps://whyu.me/reclor/
@inproceedings{yu2020reclor,
author = {Yu, Weihao and Jiang, Zihang and Dong, Yanfei and Feng, Jiashi},
title = {ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning},
booktitle = {International Conference on Learning Representations (ICLR)},
month = {April},
year = {2020}
}
bigbenchBIG-Bench but it doesn't require the hellish dependencies (tensorflow, pypi-bigbench, protobuf) of the official version.
dataset = load_dataset("tasksource/bigbench",'movie_recommendation')
Code to reproduce:
https://colab.research.google.com/drive/1MKdLdF7oqrSQCeavAcsEnPdI85kD0LzU?usp=sharing
Datasets are capped to 50k examples to keep things light.
I also removed the default split when train was available also to save space, as default=train+val.
@article{srivastava2022beyond… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/bigbench.HF_ML_Tasksmith
HF ML Tasksmith
Fifty PR-derived Harbor tasks from Accelerate, Diffusers, PEFT, Transformers and TRL, including CPU and GPU tasks.
Contains 50 Harbor tasks generated with the owned
tasksmith recipe in Repo2RLEnv.
Browse the complete task bundles in Harbor Visualiser or
open the task folders. Each folder is a runnable Harbor task:
tasks/<task_id>/
├── task.toml # Harbor configuration and provenance
├── instruction.md # Task shown to the coding agent… See the full description on the dataset page: https://huggingface.co/datasets/FineEnvs/HF_ML_Tasksmith.