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README.md

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@@ -133,7 +133,7 @@ I added *ELD-L* for comparison, which has a 2.3x bigger database, but only incre
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Here is the average, per test, of Tweets, Big test & Sentences.
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![Sentences tests average](https://raw.githubusercontent.com/nitotm/efficient-language-detector/main/benchmarks/sentences_avg_py.png)
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![Sentences tests average](https://raw.githubusercontent.com/nitotm/efficient-language-detector-py/main/benchmarks/sentences_avg_py.png)
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<!--- Sentences average
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| | Time | Accuracy |
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|:--------------------|:------------:|:------------:|
@@ -163,4 +163,4 @@ Full name languages:
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- Train from bigger datasets, and more languages.
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- The tokenizer could separate characters from languages that have their own alphabet, potentially improving accuracy and reducing the N-grams database. Retraining and testing is needed.
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If you wish to Donate for open source improvements, Hire me for private modifications / upgrades, or to Contact me, use the following link: https://linktr.ee/nitotm
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If you wish to Donate for open source improvements, Hire me for private modifications / upgrades, or to Contact me, use the following link: https://linktr.ee/nitotm

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