lchaloupsky
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Update README.md
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README.md
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@@ -1,7 +1,7 @@
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---
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language: cs
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widget:
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-
- text:
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license: mit
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datasets:
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- oscar
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@@ -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 = "
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inputs = tokenizer(text, return_tensors="pt")
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# model output
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@@ -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 = "
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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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@@ -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 = "
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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:
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- 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
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