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license: mit |
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widget: |
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- text: বহুল আলোচিত দশম জাতীয় সংসদ |
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- text: গাজীপুরের কালিয়াকৈর উপজেলার তেলিরচালা |
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--- |
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Bangla GPT2 model was trained using the Bangla Newspaper dataset. Here we used prothom alo 250mb data for GPT2 model training and also vocab size 50k. |
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Github link : https://github.com/saiful9379/Bangla_GPT2 |
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```py |
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from transformers import TFGPT2LMHeadModel, GPT2Tokenizer |
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tokenizer = GPT2Tokenizer.from_pretrained("saiful9379/Bangla_GPT2") |
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model = TFGPT2LMHeadModel.from_pretrained("saiful9379/Bangla_GPT2") |
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text = "বহুল আলোচিত দশম জাতীয় সংসদ" |
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input_ids = tokenizer.encode(text, return_tensors='tf') |
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print(input_ids) |
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output = model.generate( |
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input_ids, |
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max_length=175, |
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num_beams=10, |
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temperature=0.7, |
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no_repeat_ngram_size=2, |
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num_return_sequences=5 |
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) |
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predicted_text = tokenizer.decode(output[0], skip_special_tokens=True) |
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print(predicted_text) |
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``` |
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Here is the basic configuration of Bangla GPT2 Model, |
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``` |
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vocab_size = 50000 |
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block_size = 200 |
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learning_rate=3e-5 |
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num_epoch = 100 |
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batch_size = 12 |
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buffer_size = 1000 |
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``` |