Hugging Face is a platform for sharing machine learning models, model weights, datasets, etc. The models have been trained on large amounts of data and fine-tuned to solve various problems. By downloading these pre-trained models, developers can save a significant amount of time and resources that would otherwise be required to train models from scratch. This tutorial explains how to download files from Hugging Face using Python.
- Install the following package using
pip install huggingface
In the following code, we use the
hf_hub_download function to download a specific file from a Hugging Face repository and save it in the local directory.
from huggingface_hub import hf_hub_download hf_hub_download( repo_id='google/mobilenet_v2_1.0_224', filename='pytorch_model.bin', local_dir='models/mobilenet_v2_1.0_224', local_dir_use_symlinks=False )
Here is an explanation of the parameters used in the function:
|Specifies the repository ID in the Hugging Face from which we want to download the file (e.g. google/mobilenet_v2_1.0_224).|
|Specifies the name of the file we want to download (e.g. pytorch_model.bin).|
|Specifies the local directory where we want to save the downloaded file.|
|Specifies how the file must be saved in your local directory. If set to |
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