NeuralBridgeDocumentation

plamo embedding 1b

unofficialembedding
DeveloperPfnet
Identifierpfnet/plamo-embedding-1b-08130

plamo embedding 1b specifications

Context window
Max output tokens
Release date
InputText
OutputVector

plamo embedding 1b pricing in rubles

You pay for what you use, per token and per unit. The final request cost is returned in the API response.

TypePrice
Input tokens2,47per 1M tokens

Prices are in rubles and may change with exchange rates.

What plamo embedding 1b can do

plamo embedding 1b API: connection and code examples

The service exposes a single OpenAI-compatible API. Set our base_url and the key from your dashboard.

OpenAI Python SDK

from openai import OpenAI

client = OpenAI(api_key="YOUR_API_KEY", base_url="https://api.neuralbridge.ru/v1")

result = client.embeddings.create(model="pfnet/plamo-embedding-1b-08130", input="Текст для векторизации")

print(len(result.data[0].embedding))

cURL

curl https://api.neuralbridge.ru/v1/embeddings \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "pfnet/plamo-embedding-1b-08130", "input": "Текст для векторизации"}'

API endpoints

POST /v1/embeddingsprimaryEmbeddings
Вектарнае прадстаўленне тэксту для пошуку, кластарызацыі і ацэнкі блізкасці.

Supported request parameters

ParameterDefaultAllowed valuesDescription
dimensionsПамер вектара эмбеддинга: карацейшы вектар — менш месца і хутчэй пошук, але грубейшае падабенства.
encoding_formatfloatЯк аддаць вектар: масівам лікаў або радком base64.
Language:РусскийEnglishУкраїнськаБеларускаяҚазақшаOʻzbekchaКыргызчаТоҷикӣՀայերենAzərbaycancaTürkmençeRomânăDeutschFrançaisEspañolItalianoPortuguêsPolskiNederlandsTürkçeΕλληνικά