tulu-3
Datasets
All datasets matching “tulu-3”tulu-3-sft-mixture
Tulu 3 SFT Mixture
Note that this collection is licensed under ODC-BY-1.0 license; different licenses apply to subsets of the data. Some portions of the dataset are non-commercial. We present the mixture as a research artifact.
The Tulu 3 SFT mixture was used to train the Tulu 3 series of models.
It contains 939,344 samples from the following sets:
CoCoNot (ODC-BY-1.0), 10,983 prompts (Brahman et al., 2024)
FLAN v2 via ai2-adapt-dev/flan_v2_converted, 89,982 prompts (Longpre et… See the full description on the dataset page: https://huggingface.co/datasets/allenai/tulu-3-sft-mixture.tulu-3-sft-personas-instruction-following
Dataset Descriptions
This dataset contains 29980 examples and is synthetically created to enhance model's capabilities to follow instructions precisely and to satisfy user constraints. The constraints are borrowed from the taxonomy in IFEval dataset.
To generate diverse instructions, we expand the methodology in Ge et al., 2024 by using personas. More details and exact prompts used to construct the dataset can be found in our paper.
Curated by: Allen Institute for AI
Paper: TBD… See the full description on the dataset page: https://huggingface.co/datasets/allenai/tulu-3-sft-personas-instruction-following.tulu-3-sft-personas-math
A filtered version of this dataset is available here: https://huggingface.co/datasets/allenai/tulu-3-sft-personas-math-filtered
Dataset Descriptions
This dataset contains 149960 examples and is synthetically created to enhance model's capabilities to answer complex and hard math word problems.
To generate diverse math questions, we expand the methodology in Ge et al., 2024 by using personas. More details and exact prompts used to construct the dataset can be found in our paper.… See the full description on the dataset page: https://huggingface.co/datasets/allenai/tulu-3-sft-personas-math.tulu-3-sft-personas-code
Dataset Descriptions
This dataset contains 34999 examples and is synthetically created to enhance models' coding capabilities.To generate diverse python coding questions, we expand the methodology in Ge et al., 2024 by using personas to ground the code completion question in real-world scenarios. More details and exact prompts used to construct the dataset can be found in our paper.
Curated by: Allen Institute for AI
Paper: TBD
Repository: TBD
Language(s) (NLP): English
License:… See the full description on the dataset page: https://huggingface.co/datasets/allenai/tulu-3-sft-personas-code.tulu-3-sft-olmo-2-mixture-0225Used to train OLMo 2 32B. From the blog post:
Filtered out instructions from the SFT dataset and the chosen responses of the preference data that included mentions of a date cutoff from the synthetic data generation process. This resulted in a new version of the instruction dataset, Tulu 3 SFT Mixture 0225, and preference dataset, OLMo-2-32B-pref-mix-0325.
We use majority voting to improve the quality of answers to our synthetic math questions. For our Persona MATH and Grade School Math… See the full description on the dataset page: https://huggingface.co/datasets/allenai/tulu-3-sft-olmo-2-mixture-0225.tulu-3-sft-olmo-2-mixtureNote that this collection is licensed under ODC-BY-1.0 license; different licenses apply to subsets of the data. Some portions of the dataset are non-commercial. We present the mixture as a research artifact.
The OLMo v2 SFT mixture was used to train the OLMo models.
It contains 939,344 samples from the following sets:
CoCoNot (ODC-BY-1.0), 10,983 prompts (Brahman et al., 2024)
FLAN v2 via ai2-adapt-dev/flan_v2_converted, 89,982 prompts (Longpre et al., 2023)
No Robots (CC-BY-NC-4.0), 9,500… See the full description on the dataset page: https://huggingface.co/datasets/allenai/tulu-3-sft-olmo-2-mixture.