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@@ -16,7 +16,7 @@ The demo can be found [here](https://huggingface.co/spaces/flax-community/gpt2-i
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  You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we set a seed for reproducibility:
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  ```python
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  >>> from transformers import pipeline, set_seed
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- >>> generator = pipeline('text-generation', model='flax-community/gpt2-small-indonesian')
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  >>> set_seed(42)
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  >>> generator("Sewindu sudah kita tak berjumpa,", max_length=30, num_return_sequences=5)
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@@ -32,8 +32,8 @@ Tuhan akan memberi lebih dari apa yang kita'}]
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  Here is how to use this model to get the features of a given text in PyTorch:
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  ```python
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  from transformers import GPT2Tokenizer, GPT2Model
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- tokenizer = GPT2Tokenizer.from_pretrained('flax-community/gpt2-small-indonesian')
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- model = GPT2Model.from_pretrained('flax-community/gpt2-small-indonesian')
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  text = "Ubah dengan teks apa saja."
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  encoded_input = tokenizer(text, return_tensors='pt')
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  output = model(**encoded_input)
@@ -42,8 +42,8 @@ output = model(**encoded_input)
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  and in TensorFlow:
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  ```python
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  from transformers import GPT2Tokenizer, TFGPT2Model
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- tokenizer = GPT2Tokenizer.from_pretrained('flax-community/gpt2-small-indonesian')
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- model = TFGPT2Model.from_pretrained('flax-community/gpt2-small-indonesian')
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  text = "Ubah dengan teks apa saja."
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  encoded_input = tokenizer(text, return_tensors='tf')
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  output = model(encoded_input)
 
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  You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we set a seed for reproducibility:
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  ```python
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  >>> from transformers import pipeline, set_seed
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+ >>> generator = pipeline('text-generation', model='flax-community/gpt2-medium-indonesian')
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  >>> set_seed(42)
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  >>> generator("Sewindu sudah kita tak berjumpa,", max_length=30, num_return_sequences=5)
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  Here is how to use this model to get the features of a given text in PyTorch:
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  ```python
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  from transformers import GPT2Tokenizer, GPT2Model
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+ tokenizer = GPT2Tokenizer.from_pretrained('flax-community/gpt2-medium-indonesian')
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+ model = GPT2Model.from_pretrained('flax-community/gpt2-medium-indonesian')
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  text = "Ubah dengan teks apa saja."
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  encoded_input = tokenizer(text, return_tensors='pt')
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  output = model(**encoded_input)
 
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  and in TensorFlow:
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  ```python
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  from transformers import GPT2Tokenizer, TFGPT2Model
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+ tokenizer = GPT2Tokenizer.from_pretrained('flax-community/gpt2-medium-indonesian')
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+ model = TFGPT2Model.from_pretrained('flax-community/gpt2-medium-indonesian')
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  text = "Ubah dengan teks apa saja."
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  encoded_input = tokenizer(text, return_tensors='tf')
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  output = model(encoded_input)