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Model: hakanbogan/gpt2-turkish-cased
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2026-07-17 07:30:10 +08:00
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---
language: "tr"
tags:
- turkish
- tr
- gpt2-tr
- gpt2-turkish
---
# 🇹🇷 Turkish GPT-2 Model
In this repository I release GPT-2 model, that was trained on various texts for Turkish.
The model is meant to be an entry point for fine-tuning on other texts.
## Training corpora
I used a Turkish corpora that is taken from oscar-corpus.
It was possible to create byte-level BPE with Tokenizers library of Huggingface.
With the Tokenizers library, I created a 52K byte-level BPE vocab based on the training corpora.
After creating the vocab, I could train the GPT-2 for Turkish on two 2080TI over the complete training corpus (five epochs).
Logs during training:
https://tensorboard.dev/experiment/3AWKv8bBTaqcqZP5frtGkw/#scalars
## Model weights
Both PyTorch and Tensorflow compatible weights are available.
| Model | Downloads
| --------------------------------- | ---------------------------------------------------------------------------------------------------------------
| `hakanbogan/gpt2-turkish-cased` | [`config.json`](https://huggingface.co/hakanbogan/gpt2-turkish-cased/resolve/main/config.json) • [`merges.txt`](https://huggingface.co/hakanbogan/gpt2-turkish-cased/resolve/main/merges.txt) • [`pytorch_model.bin`](https://huggingface.co/hakanbogan/gpt2-turkish-cased/resolve/main/pytorch_model.bin) • [`special_tokens_map.json`](https://huggingface.co/hakanbogan/gpt2-turkish-cased/resolve/main/special_tokens_map.json) • [`tf_model.h5`](https://huggingface.co/hakanbogan/gpt2-turkish-cased/resolve/main/tf_model.h5) • [`tokenizer_config.json`](https://huggingface.co/hakanbogan/gpt2-turkish-cased/resolve/main/tokenizer_config.json) • [`traning_args.bin`](https://huggingface.co/hakanbogan/gpt2-turkish-cased/resolve/main/training_args.bin) • [`vocab.json`](https://huggingface.co/hakanbogan/gpt2-turkish-cased/resolve/main/vocab.json)
## Using the model
The model itself can be used in this way:
``` python
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("hakanbogan/gpt2-turkish-cased")
model = AutoModelWithLMHead.from_pretrained("hakanbogan/gpt2-turkish-cased")
```
Here's an example that shows how to use the great Transformers Pipelines for generating text:
``` python
from transformers import pipeline
pipe = pipeline('text-generation', model="hakanbogan/gpt2-turkish-cased",
tokenizer="hakanbogan/gpt2-turkish-cased", config={'max_length':800})
text = pipe("Akşamüstü yolda ilerlerken, ")[0]["generated_text"]
print(text)
```
### How to clone the model repo?
```
git lfs install
git clone https://huggingface.co/hakanbogan/gpt2-turkish-cased
```
## Contact (Bugs, Feedback, Contribution and more)
For questions about the GPT2-Turkish model, just open an issue [here](https://github.com/hakanbogan/gpt2-turkish/issues) 🤗

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{
"activation_function": "gelu_new",
"architectures": [
"GPT2LMHeadModel"
],
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"embd_pdrop": 0.1,
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"gradient_checkpointing": false,
"initializer_range": 0.02,
"layer_norm_epsilon": 1e-05,
"model_type": "gpt2",
"n_ctx": 1024,
"n_embd": 768,
"n_head": 12,
"n_inner": null,
"n_layer": 12,
"n_positions": 1024,
"resid_pdrop": 0.1,
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"max_length": 50
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},
"vocab_size": 50257
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{
"tags":[
"tr",
"turkish",
"gpt2-tr",
"gpt2-turkish"
],
"languages":[
"tr"
]
}

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