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模型:

bigscience/bloomz-7b1-p3

任务:

文本生成

类库:

PyTorch Transformers

数据集:

Muennighoff/P3 3AMuennighoff/P3

语言:

ak

其他:

bloom Eval Results text-generation-inference

预印本库:

arxiv:2211.01786

许可:

bigscience-bloom-rail-1.0
模型介绍 文件清单
文件路径: bigscience/bloomz-7b1-p3 / evaluation_bloomz-7b1-p3 / evaluation_val
pubmed_qa
2022-10-09 20:42:08
art
2022-10-09 20:42:08
riddle_sense
2022-10-09 20:42:08
scicite
2022-10-09 20:42:08
banking77
2022-10-09 20:42:08
selqa
2022-10-09 20:42:08
blbooksgenre
2022-10-09 20:42:08
blimp
2022-10-09 20:42:08
snips_built_in_intents
2022-10-09 20:42:08
climate_fever
2022-10-09 20:42:08
wmt14_hi_en
2022-10-09 20:42:08
codah
2022-10-09 20:42:08
commonsense_qa
2022-10-09 20:42:08
conv_ai_3
2022-10-09 20:42:08
craigslist_bargains
2022-10-09 20:42:08
amazon_reviews_multi
2022-10-09 20:42:08
emotion
2022-10-09 20:42:08
financial_phrasebank
2022-10-09 20:42:08
glue
2022-10-09 20:42:08
head_qa
2022-10-09 20:42:08
health_fact
2022-10-09 20:42:08
hlgd
2022-10-09 20:42:08
hyperpartisan_news_detection
2022-10-09 20:42:08
liar
2022-10-09 20:42:08
lince
2022-10-09 20:42:08
math_qa
2022-10-09 20:42:08
movie_rationales
2022-10-09 20:42:08
aqua_rat
2022-10-09 20:42:08
mwsc
2022-10-09 20:42:08
onestop_english
2022-10-09 20:42:08
poem_sentiment
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=mlsum_es.templates=layman_summ_es.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:40.json
6.79 KB
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=mlsum_es.templates=palm_prompt.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:40.json
6.64 KB
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=mlsum_es.templates=summarise_this_in_es_few_sentences.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:40.json
6.59 KB
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_fr_en.templates=a_good_translation-en-fr-source+target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:43.json
945 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_fr_en.templates=a_good_translation-en-fr-target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:43.json
923 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_fr_en.templates=a_good_translation-fr-en-source+target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:38.json
945 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_fr_en.templates=a_good_translation-fr-en-target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:38.json
926 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_fr_en.templates=gpt3-en-fr.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:43.json
883 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_fr_en.templates=gpt3-fr-en.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:38.json
882 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_fr_en.templates=version-en-fr-target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:43.json
920 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_fr_en.templates=version-fr-en-target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:38.json
921 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_fr_en.templates=xglm-en-fr-target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:43.json
858 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_fr_en.templates=xglm-fr-en-target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:38.json
858 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_hi_en.templates=a_good_translation-en-hi-source+target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:38.json
946 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_hi_en.templates=a_good_translation-en-hi-target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:38.json
922 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_hi_en.templates=a_good_translation-hi-en-source+target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:38.json
943 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_hi_en.templates=a_good_translation-hi-en-target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:38.json
925 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_hi_en.templates=version-en-hi-target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:38.json
921 B
2022-10-09 20:42:08
agg.limited=3000.model=p31lossseqglobal_step1000.task=wmt14_hi_en.templates=version-hi-en-target.fewshot=0.batchsize=16.seed=1234.timestamp=2022-09-09T23:48:38.json
921 B
2022-10-09 20:42:08

作者:

BigScience Workshop

数据集大小:

13.19 GB

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