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Update README.md

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  1. README.md +4 -4
README.md CHANGED
@@ -1,7 +1,7 @@
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  ---
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  language: cs
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  widget:
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- - text: Praha je krásné město
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  license: mit
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  datasets:
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  - oscar
@@ -56,7 +56,7 @@ model.eval() # disable dropout (or leave in train mode to finetune)
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  ### Generate one word
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  ```python
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  # input sequence
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- text = "Praha je krásné město"
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  inputs = tokenizer(text, return_tensors="pt")
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  # model output
@@ -73,7 +73,7 @@ print('predicted text:', predicted_text)
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  ### Generate one full sequence
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  ```python
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  # input sequence
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- text = "Praha je krásné město"
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  inputs = tokenizer(text, return_tensors="pt") # tokenizer.encode(text, return_tensors="pt") directly for input_ids
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  # model output using Top-k sampling text generation method
@@ -111,7 +111,7 @@ model.eval() # disable dropout (or leave in train mode to finetune)
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  ### Generate one full sequence
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  ```python
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  # input sequence
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- text = "Praha je krásné město"
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  input_ids = tokenizer.encode(text, return_tensors="tf")
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  # model output using Top-k sampling text generation method
 
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  ---
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  language: cs
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  widget:
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+ - text: Univerzita je základem
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  license: mit
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  datasets:
7
  - oscar
 
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  ### Generate one word
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  ```python
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  # input sequence
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+ text = "Univerzita je základem"
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  inputs = tokenizer(text, return_tensors="pt")
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  # model output
 
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  ### Generate one full sequence
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  ```python
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  # input sequence
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+ text = "Univerzita je základem"
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  inputs = tokenizer(text, return_tensors="pt") # tokenizer.encode(text, return_tensors="pt") directly for input_ids
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  # model output using Top-k sampling text generation method
 
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  ### Generate one full sequence
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  ```python
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  # input sequence
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+ text = "Univerzita je základem"
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  input_ids = tokenizer.encode(text, return_tensors="tf")
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  # model output using Top-k sampling text generation method