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T0pp

BigScience's 11B multitask-prompted model that proved zero-shot generalization.

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About

T0pp (T Zero Plus Plus) is the flagship 11-billion-parameter checkpoint of BigScience's T0 family, released in 2022. It fine-tunes the T5-XXL backbone on P3, a massive collection of prompted datasets, and was the model the authors recommended as the best all-round performer. T0pp demonstrated that large-scale multitask prompted training unlocks strong zero-shot performance on unseen tasks, a direct precursor to the instruction-tuning era.

The model is fully open on Hugging Face (bigscience/T0pp) under Apache 2.0. As an encoder-decoder it is suited to understanding and generation tasks with explicit prompts rather than open-ended chat. Release date is era-level (late 2021 paper, 2022 public checkpoints).

Specs

Context window

Pricing

Free quota

API access

Weights

Open weights

Released

October 1, 2021

Benchmarks

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

instruction-followingzero-shot-nlpresearchtext-generationmultitask

Trust score — 7/10

/10 trustMetrics-checked

Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 119; Trending score 72/100 from researcher assessment.

Sources