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tFINE-850m-24x24-1024ctx

Pretrained T5 model with nanoT5:

~850m parameters, 24 layers in encoder, 24 layers in decoder
sentencepiece tokenizer with 48k vocab & byte-pair fallback
- handles whitespaces etc correctly (unlike original T5 tokenizer)
1024 ctx during pretrain
relative_attention_num_buckets increased to 48 from 32 for context length upscaling

Experiment logs

Training consisted of two phases:

TODO
TODO

Downloads last month: 1

Safetensors

Model size

854M params

Tensor type

F32

Inference Examples

Text2Text Generation

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Dataset used to train pszemraj/tFINE-850m-24x24-1024ctx

Collection including pszemraj/tFINE-850m-24x24-1024ctx

tFINE

Collection

pretrained t5 models on high quality data(e.g. fineweb) • 2 items • Updated 2 days ago