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README.md
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# sinhala-gpt2
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This particular model has undergone fine-tuning based on the [gpt2](https://huggingface.co/gpt2) architecture, utilizing a dataset of Sinhala NEWS from various sources.
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Even though this is quite simple to train, it is still capable of generating news articles that are identical. Take, for example, the following samples(Some of them are hilarious though :D):
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- "ඔබ විසින් මෙම විරෝධතාව සංවිධානය කර තිබුණේ නැහැ කියලා හිටපු ජනාධිපති මහ"
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- "දුර්ලභ ගණයේ විශ්වවිද්යාල ප්රතිපාදන කොමිෂන් සභාවේ සභාපති මහාචාර්ය ජී එල්"
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⚠️ Since the dataset used for this model is mostly composed of news articles, it is heavily biased toward generating news content. This bias may become apparent during the generation process.
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## Training procedure
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The model was trained for 12+ hours on Kaggle GPUs.
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tokenizer = AutoTokenizer.from_pretrained("Ransaka/sinhala-gpt2")
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model = AutoModelForCausalLM.from_pretrained("Ransaka/sinhala-gpt2")
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generator("දුර")
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```
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or using git
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```bash
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# sinhala-gpt2
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This particular model has undergone fine-tuning based on the [gpt2](https://huggingface.co/gpt2) architecture, utilizing a dataset of Sinhala NEWS from various sources.
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## Training procedure
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The model was trained for 12+ hours on Kaggle GPUs.
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tokenizer = AutoTokenizer.from_pretrained("Ransaka/sinhala-gpt2")
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model = AutoModelForCausalLM.from_pretrained("Ransaka/sinhala-gpt2")
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generator("දුර")
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```
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or using git
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```bash
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