replicate
/
all-mpnet-base-v2
This is a language model that can be used to obtain document embeddings suitable for downstream tasks like semantic search and clustering.
If you haven’t yet trained a model on Replicate, we recommend you read one of the following guides.
Pricing
Trainings for this model run on Nvidia T4 GPU hardware, which costs $0.000225 per second.
Create a training
Install the Python library:
pip install replicate
Then, run this to create a training with replicate/all-mpnet-base-v2:b6b7585c as the base model:
import replicate
training = replicate.trainings.create(
version="replicate/all-mpnet-base-v2:b6b7585c9640cd7a9572c6e129c9549d79c9c31f0d3fdce7baac7c67ca38f305",
input={
...
},
destination=f"{username}/<destination-model-name>"
)
print(training)
curl -s -X POST \
-d '{"destination": "{username}/<destination-model-name>", "input": {...}}' \
-H "Authorization: Bearer $REPLICATE_API_TOKEN" \
https://api.replicate.com/v1/models/replicate/all-mpnet-base-v2/versions/b6b7585c9640cd7a9572c6e129c9549d79c9c31f0d3fdce7baac7c67ca38f305/trainings
The API response will look like this:
{
"id": "zz4ibbonubfz7carwiefibzgga",
"version": "b6b7585c9640cd7a9572c6e129c9549d79c9c31f0d3fdce7baac7c67ca38f305",
"status": "starting",
"input": {
"data": "..."
},
"output": null,
"error": null,
"logs": null,
"started_at": null,
"created_at": "2023-03-28T21:47:58.566434Z",
"completed_at": null
}
Note that before you can create a training, you’ll need to create a model and use its name as the value for the destination field.