HuggingInfo

Unofficial library to retrieve information from the HuggingFace website.

Installation

1npm install @bocchilorenzo/hugginginfo

Usage

1const HuggingInfo = require("@bocchilorenzo/hugginginfo");
2const hf = new HuggingInfo();

Methods

getTasks()

Fetches the tasks available from the Huggingface model hub (on the left of the page at huggingface.co/models). Returns a promise that resolves to an object.

1hf.getTasks().then((tasks) => {
2    console.log(tasks);
3});

Example response:

1{
2    "url": "https://huggingface.co/models",
3    "tasks": {
4        {
5            "name": "Feature Extraction",
6            "url": "/models?pipeline_tag=feature-extraction"
7        },
8        {
9            "name": "Text-to-Image",
10            "url": "/models?pipeline_tag=text-to-image"
11        }
12        ...
13    }
14}

getModelList()

Fetches the model list from the Huggingface model hub for a certain task. Parameters:

• task: The task to fetch models for. Must be filled with a valid task.
• sortBy: The field to sort by. Defaults to "downloads".
• page: The page to fetch. Defaults to 0.

Returns a promise that resolves to an object.

1hf.getModelList("fill-mask").then((models) => {
2    console.log(models);
3});

Example response:

1{
2  "url": "https://huggingface.co/models?pipeline_tag=fill-mask&sort=downloads&p=0",
3  "totalModels": 5738,
4  "models": [
5    {
6      "name": "bert-base-uncased",
7      "lastUpdated": "Nov 16, 2022",
8      "downloads": "31.7M",
9      "likes": "523"
10    },
11    {
12      "name": "emilyalsentzer/Bio_ClinicalBERT",
13      "lastUpdated": "Feb 27, 2022",
14      "downloads": "12.2M",
15      "likes": "70"
16    },
17    ...
18  ],
19  "nextPage": 1
20}

getModelInfo()

Fetches model information from the Huggingface model hub. Parameters:

• name: The name of the model.

Returns a promise that resolves to an object.

1hf.getModelInfo("bert-base-uncased").then((model) => {
2    console.log(model);
3});

Example response:

1{
2  "url": "https://huggingface.co/bert-base-uncased",
3  "name": "bert-base-uncased",
4  "shortDescription": "Pretrained model on English language using a masked language modeling (MLM) objective. It was introduced in this paper and first released in this repository. This model is uncased: it does not make a difference between english and English.",
5  "downloads": 31684957,
6  "likes": 523,
7  "tags": [
8    "Fill-Mask",
9    "PyTorch",
10    "TensorFlow",
11    "JAX",
12    "Rust",
13    "Safetensors",
14    "Transformers",
15    "bookcorpus",
16    "wikipedia",
17    "English",
18    "arxiv:1810.04805",
19    "bert",
20    "exbert",
21    "AutoTrain Compatible"
22  ],
23  "license": "apache-2.0",
24  "fillType": "[MASK]"
25}

Note

This library is not affiliated with Huggingface in any way. All the information is retrieved from the Huggingface website. If you want to use this library in a project, please make sure to follow the Huggingface Terms of Service.