[whatmodel.sh](../../README.md) / BLOOMZ 560M # BLOOMZ 560M BigScience · released 2022-11 · 0.559B params · bigscience-bloom-rail-1.0 **score 14.4** ±3.8 · comparison only: no current run option verified · from 6 benchmark results across 3 sources Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at _{● marks BLOOMZ 560M among every model on that task or test, worst to best.}

task    vs the others      rank  counts  tests
coding  ●···▄·▄·▄··▄   #6 of 6*     63%      1

coding · #6 of 6 · 63% of its score

test               result  vs the others in its run  difficulty        counts  why
HumanEval (maker)    2.2%  ●█··█··█·█·█ beats 0/5    medium · avg 59%     63%  sharp · too hard for it

other tests (5)

test                                result  vs the others in its run  difficulty        counts  why
WinoGrande (maker)                   49.8%  ●··▁▃·▁··▁·▃ beats 0/12   medium · avg 68%     12%  too hard for it · noisy
COPA (maker)                         51.0%  ●··█▅▃▃▅·▃▃▃ beats 0/12   easy · avg 91%       11%  at its level · noisy
MC-TACO as yes/no plausibility cl…   59.0%  ●··········▅ beats 0/4    easy · avg 75%      3.4%  blunt · at its level
Story Cloze Test (maker)             58.5%  █·▂··●··▂▂▂▃ beats 6/12   easy · avg 88%      2.6%  blunt · at its level · noisy
IndoMMLU (zero-shot)                 24.0%  ●▃▅··▃···▃▃█ beats 1/10   hard · avg 37%      1.7%  blunt · too hard for it · noisy

## How the score was worked out Each result implies a score on its own, after adjusting for how hard that test is and who ran it. The model's score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its *counts* column above; here it is added up by who ran the tests. [Method](../method.md)

source                                    results  share of the score
Crosslingual Generalization through Mul…        4   88% ▇▇▇▇▇▇▇▇▇▇▇
Do Language Models Have a Common Sense …        1    3% ▇
Large Language Models Only Pass Primary…        1    2% ▇
prior: pull toward the middle                        6% ▇
weighted average                                   = 14.4

_{Licences: Crosslingual Generalization through Multitask Finetuning ([CC BY 4.0](../../licenses/acl-2023-acl-long-891-CC-BY-4-0.txt)) · Do Language Models Have a Common Sense regarding Time? Revisiting Temporal Commonsense Reasoning in the Era of Large Language Models ([CC BY 4.0](../../licenses/acl-2023-emnlp-main-418-CC-BY-4-0.txt)) · Large Language Models Only Pass Primary School Exams in Indonesia: A Comprehensive Test on IndoMMLU ([CC BY 4.0](../../licenses/acl-2023-emnlp-main-760-CC-BY-4-0.txt))} ## How to run it No verified API or local download yet. Model repository and documentation: [huggingface.co/bigscience](https://huggingface.co/bigscience/bloomz-560m) [interactive version](https://whatmodel.sh/model/bloomz-560m) · [JSON](https://whatmodel.sh/api?format=json&all=1)