penney
lm-scorer
| penney | lm-scorer | |
|---|---|---|
| 2 | 4 | |
| 26 | 294 | |
| - | - | |
| 0.0 | 0.0 | |
| 10 days ago | about 2 years ago | |
| Python | Python | |
| MIT License | MIT License |
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penney
lm-scorer
- How to obbtain probability for entire sequence (Huggingface transformers)
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MLM vs CLM for actual language modeling
I've tried this once and found the CLM score to be a better indicator than BERT log prob for my use-case. For CLM, I had used lm-scorer.
- "simonepri/lm-scorer: Language Model based sentences scoring library" ("This package provides a simple programming interface to score sentences using different ML language models.")
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Whole sentence rather than word frequency nltk?
As in, how generally would a sentence make sense in the totality of English? You could look into language models that give probability of a sentence. You can try a library called lm-scorer.
What are some alternatives?
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