AI & Machine Learning Bearer Token

Transformer APIs REST API

Production-ready transformer model inference at scale

Transformer APIs provide high-performance REST endpoints for deploying and serving transformer-based machine learning models. The API offers pre-trained models for NLP, computer vision, and multimodal tasks, with support for custom model deployment, batching, and real-time inference. Developers use it to integrate state-of-the-art AI capabilities into applications without managing infrastructure.

Base URL https://api.transformer.rest/v1

API Endpoints

Method	Endpoint	Description
POST	`/models/text-generation`	Generate text using autoregressive language models
POST	`/models/text-classification`	Classify text into predefined categories or labels
POST	`/models/token-classification`	Perform named entity recognition and POS tagging
POST	`/models/question-answering`	Extract answers from context using question-answering models
POST	`/models/summarization`	Generate summaries from longer text documents
POST	`/models/translation`	Translate text between supported language pairs
POST	`/models/embeddings`	Generate dense vector embeddings for text inputs
POST	`/models/image-classification`	Classify images using vision transformer models
POST	`/models/object-detection`	Detect and localize objects within images
POST	`/models/image-to-text`	Generate captions and descriptions for images
GET	`/models`	List all available models with metadata and capabilities
GET	`/models/{model_id}`	Retrieve detailed information about a specific model
POST	`/models/deploy`	Deploy a custom model for inference
DELETE	`/models/{model_id}`	Remove a deployed custom model
GET	`/usage`	Retrieve API usage statistics and token consumption

Code Examples

curl -X POST https://api.transformer.rest/v1/models/text-generation \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gpt2-large",
    "prompt": "The future of AI is",
    "max_tokens": 100,
    "temperature": 0.7
  }'

const response = await fetch('https://api.transformer.rest/v1/models/text-generation', {
  method: 'POST',
  headers: {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    model: 'gpt2-large',
    prompt: 'The future of AI is',
    max_tokens: 100,
    temperature: 0.7
  })
});

const data = await response.json();
console.log(data.generated_text);

import requests

url = 'https://api.transformer.rest/v1/models/text-generation'
headers = {
    'Authorization': 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json'
}
payload = {
    'model': 'gpt2-large',
    'prompt': 'The future of AI is',
    'max_tokens': 100,
    'temperature': 0.7
}

response = requests.post(url, json=payload, headers=headers)
result = response.json()
print(result['generated_text'])

Connect Transformer APIs to AI

Deploy a Transformer APIs MCP server on IOX Cloud and connect it to Claude, ChatGPT, Cursor, or any AI client. Your AI assistant gets direct access to Transformer APIs through these tools:

generate_text Generate text completions using specified transformer models with configurable parameters like temperature and max tokens

classify_text Classify text into categories using fine-tuned classification models, returning confidence scores for each label

extract_entities Extract named entities and perform token classification on input text, identifying persons, organizations, locations, and custom entity types

generate_embeddings Create dense vector embeddings for text inputs suitable for semantic search, clustering, and similarity comparison

analyze_image Process images using vision transformers for classification, object detection, or image-to-text generation tasks

Deploy in 60 seconds

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Transformer APIs REST API

API Endpoints

Code Examples

Connect Transformer APIs to AI

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