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--- |
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datasets: |
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- phonemetransformers/IPA-CHILDES |
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language: |
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- en |
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- eu |
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- zh |
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- da |
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- nl |
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- hr |
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- es |
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- et |
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- fa |
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- fr |
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- de |
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- hu |
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- is |
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- id |
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- ga |
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- it |
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- ja |
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- ko |
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- pt |
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- pl |
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- qu |
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- ro |
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- sr |
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- sv |
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- tr |
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- cy |
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- 'no' |
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--- |
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# IPA CHILDES Models: Tiny |
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Phoneme-based GPT-2 models trained on all 31 sections of the [IPA-CHILDES](https://huggingface.co/datasets/phonemetransformers/IPA-CHILDES) dataset for the paper [BabyLM's First Words: Word Segmentation as a Phonological Probing Task](https://arxiv.org/abs/2504.03338). |
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The models have 600k non-embedding parameters and were trained on 100k tokens of their language. They were evaluated for phonological knowledge using the *word segmentation* task. Check out the paper for more details. Training and analysis scripts can be found [here](https://github.com/codebyzeb/PhonemeTransformers). |
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To load a model: |
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```python |
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from transformers import AutoModel |
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farsi_model = AutoModel.from_pretrained('phonemetransformers/ipa-childes-models-tiny', subfolder='Farsi') |
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``` |
