Datasetpublic

DaoCloud/Muse-Glimmer-OPB-100K

Muse Glimmer OPB 100K On-policy OpenPerfectBlend training data used for DaoCloud/Muse-Glimmer-30B-DSpark. Prompts are sampled from mlabonne/open-perfectblend, and assistant turns are regenerated on-policy with Muse Glimmer 30B. The dataset contains 99,984 successfully generated conversations and 148,900 train-turn rows. Responses were regenerated with Muse Glimmer 30B at four reasoning strengths. Reasoning strength Conversations Train-turn rows low 64,997 96,765… See the full description on the dataset page: https://huggingface.co/datasets/DaoCloud/Muse-Glimmer-OPB-100K.

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face

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Dataset Card

Muse Glimmer OPB 100K

On-policy OpenPerfectBlend training data used for DaoCloud/Muse-Glimmer-30B-DSpark.

Prompts are sampled from mlabonne/open-perfectblend, and assistant turns are regenerated on-policy with Muse Glimmer 30B.

The dataset contains 99,984 successfully generated conversations and 148,900 train-turn rows. Responses were regenerated with Muse Glimmer 30B at four reasoning strengths.

Reasoning strength	Conversations	Train-turn rows
low	64,997	96,765
medium	10,000	14,829
high	19,991	29,957
xhigh	4,996	7,349
Total	99,984	148,900

Schema

Field	Description
`id`	Unique train-turn ID
`primary_id`	Source conversation ID
`input_ids`	Tokenized on-policy conversation through the train turn
`loss_mask`	Token-level training mask
`reasoning_strength`	`low`, `medium`, `high`, or `xhigh`

Every row has trainable tokens. Row IDs are unique, source conversation sets are disjoint, and generation ordinals are contiguous.

File

text

muse_opb_onpolicy_100k.jsonl
1,646,393,887 bytes
SHA-256  70d68dff971d1fe00d90a356b1a1eaeac845f9a3cc2069ce525043312444439a

This release contains tokenized training examples. Use the Muse Glimmer 30B tokenizer when inspecting or converting input_ids back to text.