Sign inSign up

convmind/model-as-service

By convmind

•Updated over 5 years ago

A collection of docker image to run ML models in dockers

Image
0

500K+

convmind/model-as-service repository overview

⁠model-as-service

convmind pre-train as service

⁠BERT-as-service

pip install bert-serving-server  # server
pip install bert-serving-client  # client, independent of `bert-serving-server`

use the client:

from bert_serving.client import BertClient
bc = BertClient(ip='gpu.convmind.ai', port=6555, port_out=6556, check_version=False)
bc.encode(['First do it', 'then do it right', 'then do it better'])

⁠Hugging Face Bert HTTP server

docker run --runtime nvidia -dit -p 7000:7000 -t convmind/model-as-service:latest_hf 

⁠Stanford CoreNLP

https://stanfordnlp.github.io/CoreNLP/corenlp-server.html
⁠Dev mode

docker run -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:7.3.1

https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html⁠

Tag summary

Content type

Image

Digest

Size

393.9 MB

Last updated

over 5 years ago

docker pull convmind/model-as-service:r2base-es-7.10.1