packages/tasks/src/feature-extraction/about.md

About the Task

Feature extraction is the task of building features intended to be informative from a given dataset, facilitating the subsequent learning and generalization steps in various domains of machine learning.

Use Cases

Feature extraction can be used to do transfer learning in natural language processing, computer vision and audio models.

Inference

Feature Extraction

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

• Documentation for feature extractor of 🤗Transformers