plamo-embedding-1b

Text Embeddings • pfnet • Hosted

PLaMo-Embedding-1B is a Japanese text embedding model developed by Preferred Networks, Inc. It can convert Japanese text input into numerical vectors and can be used for a wide range of applications, including information retrieval, text classification, and clustering.

Model Info
Unit Pricing	$0.019 per M input tokens

Usage

export interface Env {
  AI: Ai;
}

export default {
  async fetch(request, env): Promise<Response> {

    // Can be a string or array of strings]
    const stories = [
      "This is a story about an orange cloud",
      "This is a story about a llama",
      "This is a story about a hugging emoji",
    ];

    const embeddings = await env.AI.run(
      "@cf/pfnet/plamo-embedding-1b",
      {
        text: stories,
      }
    );

    return Response.json(embeddings);
  },
} satisfies ExportedHandler<Env>;

import os
import requests


ACCOUNT_ID = "your-account-id"
AUTH_TOKEN = os.environ.get("CLOUDFLARE_AUTH_TOKEN")

stories = [
  'This is a story about an orange cloud',
  'This is a story about a llama',
  'This is a story about a hugging emoji'
]

response = requests.post(
  f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/pfnet/plamo-embedding-1b",
  headers={"Authorization": f"Bearer {AUTH_TOKEN}"},
  json={"text": stories}
)

print(response.json())

curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/pfnet/plamo-embedding-1b  \
  -X POST  \
  -H "Authorization: Bearer $CLOUDFLARE_API_TOKEN"  \
  -d '{ "text": ["This is a story about an orange cloud", "This is a story about a llama", "This is a story about a hugging emoji"] }'

▶text

one ofrequired

▶data[]

arrayEmbedding vectors, where each vector is a list of floats.

▶shape[]

arrayminItems: 2maxItems: 2Shape of the embedding data as [number_of_embeddings, embedding_dimension].

API Schemas

Input
Output

{
  "type": "object",
  "properties": {
    "text": {
      "oneOf": [
        {
          "type": "string"
        },
        {
          "type": "array",
          "items": {
            "type": "string"
          }
        }
      ],
      "description": "Input text to embed. Can be a single string or a list of strings."
    }
  },
  "required": [
    "text"
  ]
}

{
  "type": "object",
  "properties": {
    "data": {
      "type": "array",
      "items": {
        "type": "array",
        "items": {
          "type": "number"
        }
      },
      "description": "Embedding vectors, where each vector is a list of floats."
    },
    "shape": {
      "type": "array",
      "items": {
        "type": "integer"
      },
      "minItems": 2,
      "maxItems": 2,
      "description": "Shape of the embedding data as [number_of_embeddings, embedding_dimension]."
    }
  },
  "required": [
    "data",
    "shape"
  ]
}