Model reference · open weights

Ancient-Greek-BERT

Available as managed deployment Embeddings pranaydeeps · community Embeddings 1 variants 503 dl/mo

Ancient-Greek-BERT is an open-weight embedding model from pranaydeeps. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.

What it is

Released bypranaydeeps
TypeEmbedding models
TaskEmbeddings
Parameters (lead)113M
Context512 tokens
Runs withtransformers
Released2022-03-02
Popularity503 downloads / month
LicenceUnknown

About

What Ancient-Greek-BERT is

The first and only available Ancient Greek sub-word BERT model!

State-of-the-art post fine-tuning on Part-of-Speech Tagging and Morphological Analysis.

Pre-trained weights are made available for a standard 12 layer, 768d BERT-base model.

Further scripts for using the model and fine-tuning it for PoS Tagging are available on our Github repository!

Please refer to our paper titled: "A Pilot Study for BERT Language Modelling and Morphological Analysis for Ancient and Medieval Greek". In Proceedings of The 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2021)

Read the full model card

How to use

Requirements:

pip install transformers
pip install unicodedata
pip install flair

Can be directly used from the HuggingFace Model Hub with:

from transformers import AutoTokenizer, AutoModel
tokeniser = AutoTokenizer.from_pretrained("pranaydeeps/Ancient-Greek-BERT")
model = AutoModel.from_pretrained("pranaydeeps/Ancient-Greek-BERT")

Fine-tuning for POS/Morphological Analysis

Please refer the GitHub repository for the code and details regarding fine-tuning

Training data

The model was initialised from AUEB NLP Group's Greek BERT and subsequently trained on monolingual data from the First1KGreek Project, Perseus Digital Library, PROIEL Treebank and Gorman's Treebank

Training and Eval details

Standard de-accentuating and lower-casing for Greek as suggested in AUEB NLP Group's Greek BERT The model was trained on 4 NVIDIA Tesla V100 16GB GPUs for 80 epochs, with a max-seq-len of 512 and results in a perplexity of 4.8 on the held out test set. It also gives state-of-the-art results when fine-tuned for PoS Tagging and Morphological Analysis on all 3 treebanks averaging >90% accuracy. Please consult our paper or contact me for further questions!

Cite

If you end up using Ancient-Greek-BERT in your research, please cite the paper:

@inproceedings{ancient-greek-bert,
author = {Singh, Pranaydeep and Rutten, Gorik and Lefever, Els},
title = {A Pilot Study for BERT Language Modelling and Morphological Analysis for Ancient and Medieval Greek},
year = {2021},
booktitle = {The 5th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2021)}
}

From the published model card. Full card on the HuggingFace links in the sidebar.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys ancient-greek-bert for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (ancient-greek-bert below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/embeddings \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"ancient-greek-bert","input":"text to embed"}'

Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.

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