ONNX Model Zoo

onnx-community/hiera-base-plus-224-in1k-hf

By onnx-community · ↓ 1 · ♥ 1 · Updated 2024-10-08

What's in this repo

This page lists the files in onnx-community/hiera-base-plus-224-in1k-hf, including model.onnx, model_bnb4.onnx, model_fp16.onnx and more.

  • 8 ONNX models (.onnx files)
  • 13 files, including 8 .onnx, 3 .json, 1 .md
  • Last updated 2024-10-08

ONNX files

File Size Download
onnx/model.onnx — Download
onnx/model_bnb4.onnx — Download
onnx/model_fp16.onnx — Download
onnx/model_int8.onnx — Download
onnx/model_q4.onnx — Download
onnx/model_q4f16.onnx — Download
onnx/model_quantized.onnx — Download
onnx/model_uint8.onnx — Download

How to use

These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.

README

https://huggingface.co/facebook/hiera-base-plus-224-in1k-hf with ONNX weights to be compatible with Transformers.js.

Usage (Transformers.js)

If you haven't already, you can install the Transformers.js JavaScript library from NPM using:

npm i @huggingface/transformers

Example: Perform image classification with onnx-community/hiera-base-plus-224-in1k-hf

import { pipeline } from '@huggingface/transformers';

// Create an image classification pipeline
const classifier = await pipeline('image-classification', 'onnx-community/hiera-base-plus-224-in1k-hf');

// Classify an image
const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/tiger.jpg';
const output = await classifier(url);
console.log(output);
// [
//   { label: 'tiger, Panthera tigris', score: 0.759323239326477 },
//   { label: 'tiger cat', score: 0.08907650411128998 },
//   { label: 'lynx, catamount', score: 0.0008640264859423041 },
//   { label: 'jaguar, panther, Panthera onca, Felis onca', score: 0.0007982379174791276 },
//   { label: 'leopard, Panthera pardus', score: 0.00041627752943895757 }
// ]

Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).

Model info

image-classification transformers.js
transformers.js onnx hiera image-classification base_model:facebook/hiera-base-plus-224-in1k-hf base_model:quantized:facebook/hiera-base-plus-224-in1k-hf region:us
↓ 1 ♥ 1

Created: 2024-08-29

Updated: 2024-10-08

View on Hugging Face

Files (13)

.gitattributes
README.md
config.json
onnx/model.onnx ONNX
onnx/model_bnb4.onnx ONNX
onnx/model_fp16.onnx ONNX
onnx/model_int8.onnx ONNX
onnx/model_q4.onnx ONNX
onnx/model_q4f16.onnx ONNX
onnx/model_quantized.onnx ONNX
onnx/model_uint8.onnx ONNX
preprocessor_config.json
quantize_config.json

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