
# hmByT5 - Preliminary Language Models

Preliminary Historic Multilingual and Monolingual ByT5 Models. Following languages are currently covered:

* English (British Library Corpus - Books)
* German (Europeana Newspaper)
* French (Europeana Newspaper)
* Finnish (Europeana Newspaper)
* Swedish (Europeana Newspaper)

More details can be found in [our GitHub repository](https://github.com/stefan-it/hmByT5).

# Pretraining

We use the official JAX/FLAX example in Hugging Face Transformers to pretrain a ByT5 model on a single v3-8 TPU.
Details about the training can be found [here](https://github.com/stefan-it/hmByT5/tree/main/hmbyt5-flax).

# Evaluation on Downstream Tasks (NER)

We evaluated the hmByT5 model on downstream tasks:

| Model                                                                                                                                                                           | English AjMC | German AjMC  | French AjMC  | Finnish NewsEye | Swedish NewsEye | Dutch ICDAR  | French ICDAR | Avg. |
|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------|--------------|--------------|-----------------|-----------------|--------------|--------------|------|
| [`hmbyt5-preliminary/byt5-small-english-german-french-finnish-swedish`](https://huggingface.co/hmbyt5-preliminary/byt5-small-english-german-french-finnish-swedish)             | 85.40 ± 0.78 | 87.12 ± 0.19 | 84.41 ± 0.34 |                 |                 |              |              |      |

# Acknowledgements

Research supported with Cloud TPUs from Google's [TPU Research Cloud](https://sites.research.google/trc/about/) (TRC).
Many Thanks for providing access to the TPUs ❤️

{"language": ["en", "de", "fr", "fi", "sv"], "license": "mit"}
transformers pytorch jax tensorboard t5 text2text-generation en de fr fi sv license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #jax #tensorboard #t5 #text2text-generation #en #de #fr #fi #sv #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

hmByT5 - Preliminary Language Models
====================================


Preliminary Historic Multilingual and Monolingual ByT5 Models. Following languages are currently covered:


* English (British Library Corpus - Books)
* German (Europeana Newspaper)
* French (Europeana Newspaper)
* Finnish (Europeana Newspaper)
* Swedish (Europeana Newspaper)


More details can be found in our GitHub repository.


Pretraining
===========


We use the official JAX/FLAX example in Hugging Face Transformers to pretrain a ByT5 model on a single v3-8 TPU.
Details about the training can be found here.


Evaluation on Downstream Tasks (NER)
====================================


We evaluated the hmByT5 model on downstream tasks:



Acknowledgements
================


Research supported with Cloud TPUs from Google's TPU Research Cloud (TRC).
Many Thanks for providing access to the TPUs ️



TAGS
#transformers #pytorch #jax #tensorboard #t5 #text2text-generation #en #de #fr #fi #sv #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

TAGS
#transformers #pytorch #jax #tensorboard #t5 #text2text-generation #en #de #fr #fi #sv #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
