1,747 Downloads Updated 1 year ago
Name
8 models
enbeddrus:latest
337MB · 512 context window · Text · 1 year ago
enbeddrus:v0.1
337MB · 512 context window · Text · 1 year ago
enbeddrus:v0.2
latest337MB · 512 context window · Text · 1 year ago
enbeddrus:v0.1-domain
337MB · 512 context window · Text · 1 year ago
enbeddrus:v0.1-domain-fp16
337MB · 512 context window · Text · 1 year ago
enbeddrus:v0.1-fp16
337MB · 512 context window · Text · 1 year ago
enbeddrus:v0.2-q8_0
181MB · 512 context window · Text · 1 year ago
enbeddrus:v0.2-fp16
337MB · 512 context window · Text · 1 year ago
Note: this model requires Ollama 0.1.26 or later. Download it here. It can only be used to generate embeddings.
The Enbeddrus is embedding model designed to extract similar embeddings for comparable English and Russian phrases. It is based on the bert-base-multilingual-uncased model and was trained over 20 epochs on the following datasets:
The goal of this model is to generate identical or very similar embeddings regardless of whether the text is written in English or Russian.
There is present two versions of model:
This model is an embedding model, meaning it can only be used to generate embeddings.
REST API
curl http://localhost:11434/api/embeddings -d '{
"model": "evilfreelancer/enbeddrus",
"prompt": "The sky is blue because of Rayleigh scattering"
}'
Python library
ollama.embeddings(model='evilfreelancer/enbeddrus', prompt='The sky is blue because of rayleigh scattering')
Javascript library
ollama.embeddings({ model: 'evilfreelancer/enbeddrus', prompt: 'The sky is blue because of rayleigh scattering' })