hac541309 commited on
Commit
bc3468d
1 Parent(s): 3af127d

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +2 -0
README.md CHANGED
@@ -12,6 +12,8 @@ fastText is an open-source, free, lightweight library that allows users to learn
12
 
13
  This LID (Language IDentification) model is used to predict the language of the input text, and the hosted version (`lid218e`) was [released as part of the NLLB project](https://github.com/facebookresearch/fairseq/blob/nllb/README.md#lid-model) and can detect 217 languages. You can find older versions (ones that can identify 157 languages) on the [official fastText website](https://fasttext.cc/docs/en/language-identification.html).
14
 
 
 
15
  ## Model description
16
 
17
  fastText is a library for efficient learning of word representations and sentence classification. fastText is designed to be simple to use for developers, domain experts, and students. It's dedicated to text classification and learning word representations, and was designed to allow for quick model iteration and refinement without specialized hardware. fastText models can be trained on more than a billion words on any multicore CPU in less than a few minutes.
 
12
 
13
  This LID (Language IDentification) model is used to predict the language of the input text, and the hosted version (`lid218e`) was [released as part of the NLLB project](https://github.com/facebookresearch/fairseq/blob/nllb/README.md#lid-model) and can detect 217 languages. You can find older versions (ones that can identify 157 languages) on the [official fastText website](https://fasttext.cc/docs/en/language-identification.html).
14
 
15
+ Alternatively, a quantized version derived from this model is available. It is available as `model.ftz` . It is smaller but less accurate.
16
+
17
  ## Model description
18
 
19
  fastText is a library for efficient learning of word representations and sentence classification. fastText is designed to be simple to use for developers, domain experts, and students. It's dedicated to text classification and learning word representations, and was designed to allow for quick model iteration and refinement without specialized hardware. fastText models can be trained on more than a billion words on any multicore CPU in less than a few minutes.