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---
license: apache-2.0
datasets:
- HuggingFaceTB/smollm-corpus
language:
- en
pipeline_tag: text2text-generation
library_name: transformers
---
# tFINE-850m-24x24-1024ctx
Pretrained T5 model with [nanoT5](https://github.com/pszemraj/nanoT5/tree/fineweb-edu-test):
- ~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