File size: 1,593 Bytes
443fc2f 5ef4b4e 443fc2f 5ef4b4e 443fc2f e696b91 443fc2f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
---
license: apache-2.0
tags:
- Turkish
- turkish
language:
- tr
base_model:
- answerdotai/ModernBERT-base
pipeline_tag: fill-mask
---
# Long Context Pretrained Text Encoder For Turkish Language
<img src="https://huggingface.co/99eren99/ModernBERT-base-Turkish-uncased-mlm/resolve/main/assets/cover.jpg"
alt="drawing" width="400"/>
This is a Turkish Base uncased ModernBERT model. Since this model is uncased: it does not make a difference between turkish and Turkish.
#### ⚠ Uncased use requires manual lowercase conversion
**Don't** use the `do_lower_case = True` flag with the tokenizer. Instead, convert your text to lower case as follows:
```python
text.replace("I", "ı").lower()
```
This is due to a [known issue](https://github.com/huggingface/transformers/issues/6680) with the tokenizer.
Be aware that this model may exhibit biased predictions as it was trained primarily on crawled data, which inherently can contain various biases.
## Example Usage
```python
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained(
"99eren99/ModernBERT-base-Turkish-uncased-mlm", do_lower_case=False
)
#tokenizer.truncation_side = "right"
model = AutoModelForMaskedLM.from_pretrained(
"99eren99/ModernBERT-base-Turkish-uncased-mlm", torch_dtype="auto"
)
model.eval()
# model.to("cuda")
```
# Evaluations
-Mask Prediction Top 1 Accuracies (you can find eval scripts in "./assets" folder):
<img src="https://huggingface.co/99eren99/ModernBERT-base-Turkish-uncased-mlm/resolve/main/assets/eval_results.jpg"
alt="drawing"/>
|