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bigscience
/
bloomz-p3
like
14
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BigScience Workshop
796
Text Generation
Transformers
PyTorch
TensorBoard
Muennighoff/P3
46 languages
bloom
Eval Results
text-generation-inference
arxiv:
2211.01786
License:
bigscience-bloom-rail-1.0
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aa2424b
bloomz-p3
/
evaluation_val
/
wmt14_fr_en
4 contributors
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Muennighoff
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agg.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=a_good_translation-en-fr-source+target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:15.json
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agg.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=a_good_translation-en-fr-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:15.json
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agg.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=a_good_translation-fr-en-source+target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:32:35.json
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agg.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=a_good_translation-fr-en-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:45.json
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agg.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=gpt3-en-fr.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:41.json
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agg.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=gpt3-fr-en.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:32:48.json
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agg.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=version-en-fr-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:15.json
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agg.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=version-fr-en-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:41.json
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agg.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=xglm-en-fr-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:33.json
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agg.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=xglm-fr-en-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:32:48.json
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examples.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=a_good_translation-en-fr-source+target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:15.jsonl
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about 2 years ago
examples.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=a_good_translation-en-fr-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:15.jsonl
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about 2 years ago
examples.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=a_good_translation-fr-en-source+target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:32:35.jsonl
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about 2 years ago
examples.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=a_good_translation-fr-en-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:45.jsonl
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about 2 years ago
examples.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=gpt3-en-fr.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:41.jsonl
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about 2 years ago
examples.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=gpt3-fr-en.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:32:48.jsonl
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about 2 years ago
examples.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=version-en-fr-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:15.jsonl
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about 2 years ago
examples.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=version-fr-en-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:41.jsonl
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examples.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=xglm-en-fr-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:33.jsonl
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about 2 years ago
examples.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=xglm-fr-en-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:32:48.jsonl
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about 2 years ago
slim.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=a_good_translation-en-fr-source+target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:15.json
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about 2 years ago
slim.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=a_good_translation-en-fr-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:15.json
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about 2 years ago
slim.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=a_good_translation-fr-en-source+target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:32:35.json
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about 2 years ago
slim.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=a_good_translation-fr-en-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:45.json
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about 2 years ago
slim.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=gpt3-en-fr.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:41.json
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about 2 years ago
slim.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=gpt3-fr-en.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:32:48.json
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about 2 years ago
slim.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=version-en-fr-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:15.json
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about 2 years ago
slim.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=version-fr-en-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:41.json
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about 2 years ago
slim.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=xglm-en-fr-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:31:33.json
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slim.limited=3000.model=p31lossseq_global_step498.task=wmt14_fr_en.templates=xglm-fr-en-target.fewshot=0.batchsize=4.seed=1234.timestamp=2022-09-12T20:32:48.json
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