Installation

From NPM

npm install @huggingface/inferencenpm install @huggingface/hubnpm install @huggingface/agents

import{HfInference}from"@huggingface/inference";import{HfAgent}from"@huggingface/agents";import{createRepo,commit,deleteRepo,listFiles}from"@huggingface/hub";importtype{RepoId,Credentials}from"@huggingface/hub";

From CDN or Static hosting

<scripttype="module">import{HfInference}from'https://cdn.jsdelivr.net/npm/@huggingface/inference@2.6.4/+esm';import{createRepo,commit,deleteRepo,listFiles}from"https://cdn.jsdelivr.net/npm/@huggingface/hub@0.12.3/+esm";</script>

Deno

// esm.shimport{HfInference}from"https://esm.sh/@huggingface/inference"import{HfAgent}from"https://esm.sh/@huggingface/agents";import{createRepo,commit,deleteRepo,listFiles}from"https://esm.sh/@huggingface/hub"// or npm:import{HfInference}from"npm:@huggingface/inference"import{HfAgent}from"npm:@huggingface/agents";import{createRepo,commit,deleteRepo,listFiles}from"npm:@huggingface/hub"

Usage examples

@huggingface/inference examples

import{HfInference}from"@huggingface/inference";constHF_TOKEN="hf_...";constinference=newHfInference(HF_TOKEN);// You can also omit "model" to use the recommended model for the taskawaitinference.translation({model:'t5-base',inputs:'My name is Wolfgang and I live in Amsterdam'})awaitinference.textToImage({model:'stabilityai/stable-diffusion-2',inputs:'award winning high resolution photo of a giant tortoise/((ladybird)) hybrid, [trending on artstation]',parameters:{negative_prompt:'blurry',}})awaitinference.imageToText({data:await(awaitfetch('https://picsum.photos/300/300')).blob(),model:'nlpconnect/vit-gpt2-image-captioning',})// Using your own inference endpoint: https://hf.co/docs/inference-endpoints/constgpt2=inference.endpoint('https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/gpt2');const{ generated_text}=awaitgpt2.textGeneration({inputs:'The answer to the universe is'});

@huggingface/agents example

import{HfAgent,LLMFromHub,defaultTools}from'@huggingface/agents';constHF_TOKEN="hf_...";constagent=newHfAgent(HF_TOKEN,LLMFromHub(HF_TOKEN),[...defaultTools]);// you can generate the code, inspect it and then run itconstcode=awaitagent.generateCode("Draw a picture of a cat wearing a top hat. Then caption the picture and read it out loud.");console.log(code);constmessages=awaitagent.evaluateCode(code)console.log(messages);// contains the data// or you can run the code directly, however you can't check that the code is safe to execute this way, use at your own risk.constmessages=awaitagent.run("Draw a picture of a cat wearing a top hat. Then caption the picture and read it out loud.")console.log(messages);

@huggingface/hub examples

import{createRepo,uploadFile,deleteFiles}from"@huggingface/hub";constHF_TOKEN="hf_...";awaitcreateRepo({repo:"my-user/nlp-model",// or {type: "model", name: "my-user/nlp-test"},credentials:{accessToken:HF_TOKEN}});awaituploadFile({repo:"my-user/nlp-model",credentials:{accessToken:HF_TOKEN},// Can work with native File in browsersfile:{path:"pytorch_model.bin",content:newBlob(...)}});awaitdeleteFiles({repo:{type:"space",name:"my-user/my-space"},// or "spaces/my-user/my-space"credentials:{accessToken:HF_TOKEN},paths:["README.md",".gitattributes"]});

Formatting & testing

sudo corepack enablepnpm installpnpm -r format:checkpnpm -r lint:checkpnpm -r test

Building

pnpm -r build