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