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---
widget:
- text: "gelirken bir litre [MASK] aldım."
example_title: "ürün"
---
# turkish-tiny-bert-uncased
This is a Turkish Tiny uncased BERT model, developed to fill the gap for small-sized BERT models for Turkish. Since this model is uncased: it does not make a difference between turkish and Turkish.
#### ⚠ Uncased use requires manual lowercase conversion
Note that due to a [known issue](https://github.com/huggingface/transformers/issues/6680) with the tokenizer, the `do_lower_case = True` flag should **NOT** be used with the tokenizer. Instead, convert your text to lower case as follows:
```python
text.replace("I", "ı").lower()
```
Be aware that this model may exhibit biased predictions as it was trained primarily on crawled data, which inherently can contain various biases.
Other relevant information can be found in the [paper](https://arxiv.org/abs/2307.14134).
```python
from transformers import AutoTokenizer, BertForMaskedLM
from transformers import pipeline
model = BertForMaskedLM.from_pretrained(r"turkish-tiny-bert-uncased")
# or
# model = BertForMaskedLM.from_pretrained(r"turkish-tiny-bert-uncased", from_tf = True)
tokenizer = AutoTokenizer.from_pretrained(r"turkish-tiny-bert-uncased")
unmasker = pipeline('fill-mask', model=model, tokenizer=tokenizer)
unmasker("gelirken bir litre [MASK] aldım.")
# [{'score': 0.202457457780838,
# 'token': 2417,
# 'token_str': 'su',
# 'sequence': 'gelirken bir litre su aldım.'},
# {'score': 0.09290537238121033,
# 'token': 11818,
# 'token_str': 'benzin',
# 'sequence': 'gelirken bir litre benzin aldım.'},
# {'score': 0.07785643637180328,
# 'token': 2026,
# 'token_str': '##den',
# 'sequence': 'gelirken bir litreden aldım.'},
# {'score': 0.06889808923006058,
# 'token': 2299,
# 'token_str': '##yi',
# 'sequence': 'gelirken bir litreyi aldım.'},
# {'score': 0.03152570128440857,
# 'token': 2647,
# 'token_str': '##ye',
# 'sequence': 'gelirken bir litreye aldım.'}]
```
# Acknowledgments
- Research supported with Cloud TPUs from [Google's TensorFlow Research Cloud](https://sites.research.google/trc/about/) (TFRC). Thanks for providing access to the TFRC ❤️
- Thanks to the generous support from the Hugging Face team, it is possible to download models from their S3 storage 🤗
# License
MIT
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