This model is an export of these
Word2Vec Vectors
for
staticvectors
.
staticvectors
enables running inference in Python with NumPy. This helps it maintain solid runtime performance.
This model is a quantized version of the base model. It's using 10x256 Product Quantization.
Usage with StaticVectors
from staticvectors import StaticVectors
model = StaticVectors("neuml/word2vec-quantized")
model.embeddings(["word"])
Given that pre-trained embeddings models can get quite large, there is also a SQLite version that lazily loads vectors.
from staticvectors import StaticVectors
model = StaticVectors("neuml/word2vec-quantized/model.sqlite")
model.embeddings(["word"])
Runs of NeuML word2vec-quantized on huggingface.co
98
Total runs
0
24-hour runs
3
3-day runs
-24
7-day runs
-45
30-day runs
More Information About word2vec-quantized huggingface.co Model
word2vec-quantized huggingface.co is an AI model on huggingface.co that provides word2vec-quantized's model effect (), which can be used instantly with this NeuML word2vec-quantized model. huggingface.co supports a free trial of the word2vec-quantized model, and also provides paid use of the word2vec-quantized. Support call word2vec-quantized model through api, including Node.js, Python, http.
word2vec-quantized huggingface.co is an online trial and call api platform, which integrates word2vec-quantized's modeling effects, including api services, and provides a free online trial of word2vec-quantized, you can try word2vec-quantized online for free by clicking the link below.
NeuML word2vec-quantized online free url in huggingface.co:
word2vec-quantized is an open source model from GitHub that offers a free installation service, and any user can find word2vec-quantized on GitHub to install. At the same time, huggingface.co provides the effect of word2vec-quantized install, users can directly use word2vec-quantized installed effect in huggingface.co for debugging and trial. It also supports api for free installation.