Jina Embeddings V2 Base EN
A text embedding model with a context window of 8192 tokens and a dimensionality of 768 values.
Deploy Jina Embeddings V2 Base EN behind an API endpoint in seconds.
Deploy modelExample usage
This model takes a list of strings and returns a list of embeddings, where each embedding is a list of 768 floating-point number representing the semantic text embedding of the associated string.
Strings can be up to 8192 tokens (approximately 6000 words) in length, or shorter if max_tokens is set to a lesser value in the data dictionary.
Input
1import requests
2import os
3
4# Replace the empty string with your model id below
5model_id = ""
6baseten_api_key = os.environ["BASETEN_API_KEY"]
7
8data = {
9 "text": ["I want to eat pasta", "I want to eat pizza"],
10 "max_length": 8192
11}
12
13# Call model endpoint
14res = requests.post(
15 f"https://model-{model_id}.api.baseten.co/production/predict",
16 headers={"Authorization": f"Api-Key {baseten_api_key}"},
17 json=data
18)
19
20# Print the output of the model
21print(res.json())JSON output
1[
2 [
3 0.2593194842338562,
4 "...",
5 -1.4059709310531616
6 ],
7 [
8 0.11028853803873062,
9 "...",
10 -0.9492666125297546
11 ]
12]
