!npm
!npm


deepinfra-node

DeepInfra API is a Node.js client for the DeepInfra Inference API. It provides a simple way to interact with the DeepInfra API.
Check out the docs from here.

Installation

``bash
npm install deepinfra-api
`

Usage

$3

The Mixtral mixture of expert model, developed by Mistral AI, is an innovative experimental machine learning model that
leverages a mixture of 8 experts (MoE) within 7b models. Its release was facilitated via a torrent, and the model's
implementation remains in the experimental phase.\_

`typescript
import { Mixtral } from "deepinfra-api";
const modelName = "mistralai/Mixtral-8x22B-Instruct-v0.1";
const apiKey = "YOUR_DEEPINFRA_API_KEY";
const main = async () => {
const mixtral = new Mixtral(Mixtral, apiKey);
const body = {
input: "What is the capital of France?",
};
const output = await mixtral.generate(body);
const text = output.results[0].generated_text;
console.log(text);
};

main();
`

$3

Gte Base is an text embedding model that generates embeddings for the input text. The model is trained by Alibaba DAMO Academy.

`typescript
import { GteBase } from "deepinfra-api";

const apiKey = "YOUR_DEEPINFRA_API_KEY";
const modelName = "thenlper/gte-base";
const main = async () => {
const gteBase = new Embeddings(modelName, apiKey);
const body = {
inputs: [
"What is the capital of France?",
"What is the capital of Germany?",
"What is the capital of Italy?",
],
};
const output = await gteBase.generate(body);
const embeddings = output.embeddings[0];
console.log(embeddings);
};

main();
`

$3

SDXL requires unique parameters, therefore it requires different initialization.

`typescript
import { Sdxl } from "deepinfra-api";
import axios from "axios";
import fs from "fs";

const apiKey = "YOUR_DEEPINFRA_API_KEY";

const main = async () => {
const model = new Sdxl(apiKey);

const input = {
prompt: "The quick brown fox jumps over the lazy dog with",
};
const response = await model.generate({ input });
const { output } = response;
const image = output[0];

await axios.get(image, { responseType: "arraybuffer" }).then((response) => {
fs.writeFileSync("image.png", response.data);
});
};

main();
`

$3

`typescript
import { TextToImage } from "deepinfra-api";
import axios from "axios";
import fs from "fs";

const apiKey = "YOUR_DEEPINFRA_API_KEY";
const modelName = "stabilityai/stable-diffusion-2-1";
const main = async () => {
const model = new TextToImage(modelName, apiKey);
const input = {
prompt: "The quick brown fox jumps over the lazy dog with",
};

const response = await model.generate(input);
const { output } = response;
const image = output[0];

await axios.get(image, { responseType: "arraybuffer" }).then((response) => {
fs.writeFileSync("image.png", response.data);
});
};
main();
`

$3

`typescript
import { AutomaticSpeechRecognition } from "deepinfra-api";

const apiKey = "YOUR_DEEPINFRA_API_KEY";
const modelName = "openai/whisper-base";

const main = async () => {
const model = new AutomaticSpeechRecognition(modelName, apiKey);

const input = {
audio: path.join(__dirname, "audio.mp3"),
};
const response = await model.generate(input);
const { text } = response;
console.log(text);
};

main();
`

$3

`typescript
import { ObjectDetection } from "deepinfra-api";

const apiKey = "YOUR_DEEPINFRA_API_KEY";
const modelName = "hustvl/yolos-tiny";
const main = async () => {
const model = new ObjectDetection(modelName, apiKey);

const input = {
image: path.join(__dirname, "image.jpg"),
};
const response = await model.generate(input);
const { results } = response;
console.log(results);
};
`

$3

`typescript
import { TokenClassification } from "deepinfra-api";

const apiKey = "YOUR_DEEPINFRA_API_KEY";
const modelName = "Davlan/bert-base-multilingual-cased-ner-hrl";

const main = async () => {
const model = new TokenClassification(modelName, apiKey);

const input = {
text: "The quick brown fox jumps over the lazy dog",
};
const response = await model.generate(input);
const { results } = response;
console.log(results);
};
`

$3

`typescript
import { FillMask } from "deepinfra-api";

const apiKey = "YOUR_DEEPINFRA_API_KEY";
const modelName = "GroNLP/bert-base-dutch-cased";

const main = async () => {
const model = new FillMask(modelName, apiKey);

const body = {
input: "Ik heb een [MASK] gekocht.",
};

const { results } = await model.generate(body);
console.log(results);
};
`

$3

`typescript
import { ImageClassification } from "deepinfra-api";

const apiKey = "YOUR_DEEPINFRA_API_KEY";
const modelName = "google/vit-base-patch16-224";

const main = async () => {
const model = new ImageClassification(modelName, apiKey);

const body = {
image: path.join(__dirname, "image.jpg"),
};

const { results } = await model.generate(body);
console.log(results);
};
`

$3

`typescript
import { ZeroShotImageClassification } from "deepinfra-api";

const apiKey = "YOUR_DEEPINFRA_API_KEY";
const modelName = "openai/clip-vit-base-patch32";

const main = async () => {
const model = new ZeroShotImageClassification(modelName, apiKey);

const body = {
image: path.join(__dirname, "image.jpg"),
candidate_labels: ["dog", "cat", "car"],
};

const { results } = await model.generate(body);
console.log(results);
};
`

$3

`typescript
import { TextClassification } from "deepinfra-api";

const apiKey = "YOUR_DEEPINFRA_API_KEY";
const modelName = "ProsusAI/finbert";

const misc = async () => {
const model = new TextClassification(apiKey);

const body = {
input:
"DeepInfra emerges from stealth with $8M to make running AI inferences more affordable",
};

const { results } = await model.generate(body);
console.log(results);
};
``

Contributors

Oguz Vuruskaner

Iskren Ivov Chernev

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull
requests to us.

License

This project is licensed under the MIT License - see the LICENSE file for details.