SUMIN/HuggingFace_transformer
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Remove accidental comment (#6629)

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josephrocca
2020-08-21 19:07:32 +10:00
committed by GitHub
parent efc7460553
commit bdf7e5de92
1 changed files with 1 additions and 1 deletions
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src/transformers/generation_tf_utils.py
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@@ -177,7 +177,7 @@ class TFGenerationMixin:
tokenizer = AutoTokenizer.from_pretrained('gpt2') # Initialize tokenizer tokenizer = AutoTokenizer.from_pretrained('gpt2') # Initialize tokenizer
model = TFAutoModelWithLMHead.from_pretrained('gpt2') # Download model and configuration from S3 and cache. model = TFAutoModelWithLMHead.from_pretrained('gpt2') # Download model and configuration from S3 and cache.
input_context = 'My cute dog' # "Legal" is one of the control codes for ctrl input_context = 'My cute dog'
bad_words_ids = [tokenizer.encode(bad_word, add_prefix_space=True) for bad_word in ['idiot', 'stupid', 'shut up']] bad_words_ids = [tokenizer.encode(bad_word, add_prefix_space=True) for bad_word in ['idiot', 'stupid', 'shut up']]
input_ids = tokenizer.encode(input_context, return_tensors='tf') # encode input context input_ids = tokenizer.encode(input_context, return_tensors='tf') # encode input context
outputs = model.generate(input_ids=input_ids, max_length=100, do_sample=True, bad_words_ids=bad_words_ids) # generate sequences without allowing bad_words to be generated outputs = model.generate(input_ids=input_ids, max_length=100, do_sample=True, bad_words_ids=bad_words_ids) # generate sequences without allowing bad_words to be generated