Language detection is an important task and identification with n-gram models is an efficient and highly accurate way to do it.
This model is a quantized version of the
base language id model
. It's using 2x256 Product Quantization like the original quantized model from FastText. This shrinks this model down to 4MB with only a minor hit on accuracy.
Usage with StaticVectors
from staticvectors import StaticVectors
model = StaticVectors("NeuML/language-id-quantized")
model.predict(["What language is this text?"])
Runs of NeuML language-id-quantized on huggingface.co
989
Total runs
0
24-hour runs
0
3-day runs
2
7-day runs
528
30-day runs
More Information About language-id-quantized huggingface.co Model
language-id-quantized huggingface.co is an AI model on huggingface.co that provides language-id-quantized's model effect (), which can be used instantly with this NeuML language-id-quantized model. huggingface.co supports a free trial of the language-id-quantized model, and also provides paid use of the language-id-quantized. Support call language-id-quantized model through api, including Node.js, Python, http.
language-id-quantized huggingface.co is an online trial and call api platform, which integrates language-id-quantized's modeling effects, including api services, and provides a free online trial of language-id-quantized, you can try language-id-quantized online for free by clicking the link below.
NeuML language-id-quantized online free url in huggingface.co:
language-id-quantized is an open source model from GitHub that offers a free installation service, and any user can find language-id-quantized on GitHub to install. At the same time, huggingface.co provides the effect of language-id-quantized install, users can directly use language-id-quantized installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
language-id-quantized install url in huggingface.co: