sentence-transformers/all-MiniLM-L12-v2 cover image

sentence-transformers/all-MiniLM-L12-v2

We present a sentence transformation model that generates semantically similar sentences. Our model is based on the Sentence-Transformers architecture and was trained on a large dataset of sentence pairs. We evaluate the effectiveness of our model by measuring its ability to generate similar sentences that are close to the original sentence in meaning.

We present a sentence transformation model that generates semantically similar sentences. Our model is based on the Sentence-Transformers architecture and was trained on a large dataset of sentence pairs. We evaluate the effectiveness of our model by measuring its ability to generate similar sentences that are close to the original sentence in meaning.

Public
$0.005 / Mtoken
512

OpenAI-compatible HTTP API

DeepInfra supports the OpenAI embeddings API. The following creates an embedding vector representing the input text

curl "https://api.deepinfra.com/v1/openai/embeddings" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $DEEPINFRA_TOKEN" \
  -d '{
    "input": "The food was delicious and the waiter...",
    "model": "sentence-transformers/all-MiniLM-L12-v2",
    "encoding_format": "float"
  }'

which will return something similar to

{
  "object":"list",
  "data":[
    {
      "object": "embedding",
      "index":0,
      "embedding":[
        -0.010480394586920738,
        -0.0026091758627444506
        ...
        0.031979579478502274,
        0.02021978422999382
      ]
    }
  ],
  "model": "sentence-transformers/all-MiniLM-L12-v2",
  "usage": {
    "prompt_tokens":12,
    "total_tokens":12
  }
}

Input fields

modelstring

model name


inputarray

sequences to embed


encoding_formatstring

format used when encoding

Default value: "float"

Allowed values: float

Input Schema

Output Schema