BGE-Large-EN v1.5

BAAI v1.5 large maps text to dense vectors for retrieval, classification, clustering, semantic search, and LLM databases.

Try BGE-Large-EN v1.5

API Usage

Endpoint

BAAI/bge-large-en-v1.5

RUN INFERENCE

curl -X POST "https://aitradestore.com/api/v1/embeddings"  
 -H "Authorization: Bearer $AITRADESTORE_API_KEY"  
 -H "Content-Type: application/json"  
 -d { 
   "model": "BAAI/bge-large-en-v1.5", 
   "input": "Our solar system orbits the Milky Way galaxy at about 515,000 mph" 
  }'

JSON RESPONSE

RUN INFERENCE

from aitradestore import AiTradeStore  client = AiTradeStore()
 response = client.embeddings.create( 
 model="BAAI/bge-large-en-v1.5", 
 input="Our solar system orbits the Milky Way galaxy at about 515,000 mph", ) print(response.data[0].embedding)

JSON RESPONSE

RUN INFERENCE

import AiTradeStore from "ai-tradestore";  const aitradestore = new AiTradeStore();  const response = await aitradestore.embeddings.create({ 
   model: "BAAI/bge-large-en-v1.5", 
   input: "Our solar system orbits the Milky Way galaxy at about 515,000 mph", }); console.log(response.data[0].embedding);

JSON RESPONSE

BGE-Large-EN v1.5

BAAI v1.5 large maps text to dense vectors for retrieval, classification, clustering, semantic search, and LLM databases.

Try BGE-Large-EN v1.5

API Usage

Endpoint

BAAI/bge-large-en-v1.5

RUN INFERENCE

curl -X POST "https://aitradestore.com/api/v1/embeddings"  
 -H "Authorization: Bearer $AITRADESTORE_API_KEY"  
 -H "Content-Type: application/json"  
 -d { 
   "model": "BAAI/bge-large-en-v1.5", 
   "input": "Our solar system orbits the Milky Way galaxy at about 515,000 mph" 
  }'

JSON RESPONSE

RUN INFERENCE

from aitradestore import AiTradeStore  client = AiTradeStore()
 response = client.embeddings.create( 
 model="BAAI/bge-large-en-v1.5", 
 input="Our solar system orbits the Milky Way galaxy at about 515,000 mph", ) print(response.data[0].embedding)

JSON RESPONSE

RUN INFERENCE

import AiTradeStore from "ai-tradestore";  const aitradestore = new AiTradeStore();  const response = await aitradestore.embeddings.create({ 
   model: "BAAI/bge-large-en-v1.5", 
   input: "Our solar system orbits the Milky Way galaxy at about 515,000 mph", }); console.log(response.data[0].embedding);

JSON RESPONSE

BGE-Large-EN v1.5

BGE-Large-EN v1.5

Let's stay in touch.

Company

AI Models

Use Cases

BGE-Large-EN v1.5

API Usage

How to use BGE-Large-EN v1.5

Model details

Prompting BGE-Large-EN v1.5

Applications & Use Cases

Embeddings

BGE-Large-EN v1.5

API Usage

How to use BGE-Large-EN v1.5

Model details

Prompting BGE-Large-EN v1.5

Applications & Use Cases

Let's stay in touch.

Company

AI Models

Use Cases