Tasks

Feature Extraction

Feature extraction is the task of extracting features learnt in a model.

Inputs
Input

India, officially the Republic of India, is a country in South Asia.

Feature Extraction Model
Output
Dimension 1 Dimension 2 Dimension 3
2.583383083343506 2.757075071334839 0.9023529887199402
8.29393482208252 1.1071064472198486 2.03399395942688
-0.7754912972450256 -1.647324562072754 -0.6113331913948059
0.07087723910808563 1.5942802429199219 1.4610432386398315

About Feature Extraction

Use Cases

Models trained on a specific dataset can learn features about the data. For instance, a model trained on an English poetry dataset learns English grammar at a very high level. This information can be transferred to a new model that is going to be trained on tweets. This process of extracting features and transferring to another model is called transfer learning. One can pass their dataset through a feature extraction pipeline and feed the result to a classifier.

Inference

from transformers import pipeline
checkpoint = "facebook/bart-base"
feature_extractor = pipeline("feature-extraction", framework="pt", model=checkpoint)
text = "Transformers is an awesome library!"

#Reducing along the first dimension to get a 768 dimensional array
feature_extractor(text,return_tensors = "pt")[0].numpy().mean(axis=0)

'''tensor([[[ 2.5834,  2.7571,  0.9024,  ...,  1.5036, -0.0435, -0.8603],
         [-1.2850, -1.0094, -2.0826,  ...,  1.5993, -0.9017,  0.6426],
         [ 0.9082,  0.3896, -0.6843,  ...,  0.7061,  0.6517,  1.0550],
         ...,
         [ 0.6919, -1.1946,  0.2438,  ...,  1.3646, -1.8661, -0.1642],
         [-0.1701, -2.0019, -0.4223,  ...,  0.3680, -1.9704, -0.0068],
         [ 0.2520, -0.6869, -1.0582,  ...,  0.5198, -2.2106,  0.4547]]])'''

Useful resources

Compatible libraries

Feature Extraction demo
Models for Feature Extraction
Browse Models (8,266)

Note A powerful feature extraction model for natural language processing tasks.

Datasets for Feature Extraction
Browse Datasets (501)

Note Wikipedia dataset containing cleaned articles of all languages. Can be used to train `feature-extraction` models.

Spaces using Feature Extraction

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Metrics for Feature Extraction

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