Tokenizers should be framework agnostic (#8599)
* Tokenizers should be framework agnostic * Run the slow tests * Not testing * Fix documentation * Apply suggestions from code review Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
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@@ -78,7 +78,7 @@ Usage Example
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torch_device = 'cuda' if torch.cuda.is_available() else 'cpu'
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tokenizer = PegasusTokenizer.from_pretrained(model_name)
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model = PegasusForConditionalGeneration.from_pretrained(model_name).to(torch_device)
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batch = tokenizer.prepare_seq2seq_batch(src_text, truncation=True, padding='longest').to(torch_device)
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batch = tokenizer.prepare_seq2seq_batch(src_text, truncation=True, padding='longest', return_tensors="pt").to(torch_device)
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translated = model.generate(**batch)
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tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)
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assert tgt_text[0] == "California's largest electricity provider has turned off power to hundreds of thousands of customers."
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