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40 lines
1.5 KiB
Markdown
40 lines
1.5 KiB
Markdown
# StackOBERTflow-comments-small
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StackOBERTflow is a RoBERTa model trained on StackOverflow comments.
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A Byte-level BPE tokenizer with dropout was used (using the `tokenizers` package).
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The model is *small*, i.e. has only 6-layers and the maximum sequence length was restricted to 256 tokens.
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The model was trained for 6 epochs on several GBs of comments from the StackOverflow corpus.
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## Quick start: masked language modeling prediction
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```python
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from transformers import pipeline
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from pprint import pprint
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COMMENT = "You really should not do it this way, I would use <mask> instead."
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fill_mask = pipeline(
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"fill-mask",
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model="giganticode/StackOBERTflow-comments-small-v1",
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tokenizer="giganticode/StackOBERTflow-comments-small-v1"
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)
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pprint(fill_mask(COMMENT))
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# [{'score': 0.019997311756014824,
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# 'sequence': '<s> You really should not do it this way, I would use jQuery instead.</s>',
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# 'token': 1738},
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# {'score': 0.01693696901202202,
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# 'sequence': '<s> You really should not do it this way, I would use arrays instead.</s>',
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# 'token': 2844},
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# {'score': 0.013411642983555794,
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# 'sequence': '<s> You really should not do it this way, I would use CSS instead.</s>',
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# 'token': 2254},
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# {'score': 0.013224546797573566,
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# 'sequence': '<s> You really should not do it this way, I would use it instead.</s>',
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# 'token': 300},
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# {'score': 0.011984303593635559,
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# 'sequence': '<s> You really should not do it this way, I would use classes instead.</s>',
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# 'token': 1779}]
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```
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