
# SSR-base

SSR-base model as in EMNLP 2021 paper [Improving Sequence-to-Sequence Pre-training via Sequence Span Rewriting](https://arxiv.org/abs/2101.00416).

{"language": ["en"], "tags": ["summarization", "text2text-generation"], "datasets": ["c4"]}
transformers pytorch t5 text2text-generation summarization en dataset:c4 arxiv:2101.00416 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #summarization #en #dataset-c4 #arxiv-2101.00416 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


# SSR-base

SSR-base model as in EMNLP 2021 paper Improving Sequence-to-Sequence Pre-training via Sequence Span Rewriting.

# SSR-base

SSR-base model as in EMNLP 2021 paper Improving Sequence-to-Sequence Pre-training via Sequence Span Rewriting.
TAGS
#transformers #pytorch #t5 #text2text-generation #summarization #en #dataset-c4 #arxiv-2101.00416 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # SSR-base

SSR-base model as in EMNLP 2021 paper Improving Sequence-to-Sequence Pre-training via Sequence Span Rewriting.
passage: TAGS
#transformers #pytorch #t5 #text2text-generation #summarization #en #dataset-c4 #arxiv-2101.00416 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# SSR-base

SSR-base model as in EMNLP 2021 paper Improving Sequence-to-Sequence Pre-training via Sequence Span Rewriting.