A library of neural encoders to convert any types of data into embeddings, dense or sparse.
python setup.py bdist_wheel
twine upload dist/*
model = EncoderLoader.load_model('pretrain-models', <model_id>, use_gpu=True, region='cn')
model.encode(['I am a good man'], show_progress_bar=True, batch_size=batch_size,)
Start a server
uvicorn soco_encoders.http.main:app --host 0.0.0.0 --port 8000 --workers 4
Start a client
res = requests.post(url='http://localhost:8000/encoder/v1/encode',
json={
"model_id": model_id,
"text": [x1] * batch_size,
'batch_size': batch_size,
"mode": "default",
"kwargs": {}
})
Start a server
python -m soco_encoders.grpc.server --host 0.0.0.0 --port 8000 --workers 4
Start a client
check out example in bench_grpc.py
Content type
Image
Digest
Size
6.3 GB
Last updated
over 4 years ago
docker pull convmind/soco-encoders:0.1-visual-cuda111