Remove downloaded tensorflow and pytorch(Hugging face) models
I would like to remove tensorflow and hugging face models from my laptop.
I did find one link https://github.com/huggingface/transformers/issues/861
but is there not command that can remove them because as mentioned in the link manually deleting can cause problems because we don't know which other files are linked to those models or are expecting some model to be present in that location or simply it may cause some error.

The transformers library will store the downloaded files in your cache. As far as I know, there is no built-in method to remove certain models from the cache. But you can code something by yourself. The files are stored with a cryptical name alongside two additional files that have .json (.h5.json in case of Tensorflow models) and .lock appended to the cryptical name. The json file contains some metadata that can be used to identify the file. The following is an example of such a file:
{&quot;url&quot;: &quot;https://cdn.huggingface.co/roberta-base-pytorch_model.bin&quot;, &quot;etag&quot;: &quot;\&quot;8a60a65d5096de71f572516af7f5a0c4-30\&quot;&quot;}

We can now use this information to create a list of your cached files as shown below:
import glob
import json
import re
from collections import OrderedDict 
from transformers import TRANSFORMERS_CACHE
 
metaFiles = glob.glob(TRANSFORMERS_CACHE + '/*.json')
modelRegex = &quot;huggingface\.co\/(.*)(pytorch_model\.bin$|resolve\/main\/tf_model\.h5$)&quot;

cachedModels = {}
cachedTokenizers = {}
for file in metaFiles:
     with open(file) as j:
         data = json.load(j)
         isM = re.search(modelRegex, data['url'])
         if isM:
             cachedModels[isM.group(1)[:-1]] = file
         else:
             cachedTokenizers[data['url'].partition('huggingface.co/')[2]] = file

cachedTokenizers = OrderedDict(sorted(cachedTokenizers.items(), key=lambda k: k[0]))

Now all you have to do is to check the keys of cachedModels and cachedTokenizers and decide if you want to keep them or not. In case you want to delete them, just check for the value of the dictionary and delete the file from the cache. Don't forget to also delete the corresponding *.json and *.lock files.
