Delete legalnlp/get_premodel.py

legalnlp/get_premodel.py

@@ -1,77 +0,0 @@
-import wget
-import zipfile
-
-
-def get_premodel(model):
-    modelv = False
-    d = None
-    if model == 'bert':
-        # BERTikal
-        url = 'https://ndownloader.figshare.com/files/30446754'
-        filename = wget.download(url, out=d)
-        if d == None:
-            d = ''
-        with zipfile.ZipFile(d+filename, "r") as zip_ref:
-            zip_ref.extractall(d+filename.replace('.zip', ''))
-        modelv = True
-    # Download files to use in Word2Vec and Doc2Vec
-    if model == 'wodc':
-        url2 = 'https://ndownloader.figshare.com/files/30446736'
-        filename2 = wget.download(url2, out=d)
-        if d == None:
-            d = ''
-        with zipfile.ZipFile(d+filename2, "r") as zip_ref:
-            zip_ref.extractall(d+filename2.replace('.zip', ''))
-        modelv = True
-    
-    # Download Word2Vec of NILC
-    if model == 'w2vnilc':
-        url2 = 'http://143.107.183.175:22980/download.php?file=embeddings/word2vec/cbow_s100.zip'
-        filename2 = wget.download(url2, out=d)
-        if d == None:
-            d = ''
-        with zipfile.ZipFile(d+filename2, "r") as zip_ref:
-            zip_ref.extractall(d+filename2.replace('.zip', ''))
-        modelv = True 
-    # Download files to use Phraser model
-    if model == 'phraser':
-        url2 = 'https://ndownloader.figshare.com/files/30446727'
-        filename2 = wget.download(url2, out=d)
-        if d == None:
-            d = ''
-        with zipfile.ZipFile(d+filename2, "r") as zip_ref:
-            zip_ref.extractall(d+filename2.replace('.zip', ''))
-        modelv = True
-    # Download files to use Fast Text model
-    if model == 'fasttext':
-        url2 = 'https://ndownloader.figshare.com/files/30446739'
-        filename2 = wget.download(url2, out=d)
-        if d == None:
-            d = ''
-        with zipfile.ZipFile(d+filename2, "r") as zip_ref:
-            zip_ref.extractall(d+filename2.replace('.zip', ''))
-        modelv = True
-    # Download files to use NeuralMind pre-model base
-    if model == 'neuralmindbase':
-        url2 = 'https://neuralmind-ai.s3.us-east-2.amazonaws.com/nlp/bert-base-portuguese-cased/bert-base-portuguese-cased_pytorch_checkpoint.zip'
-        url_vocab = 'https://neuralmind-ai.s3.us-east-2.amazonaws.com/nlp/bert-base-portuguese-cased/vocab.txt'
-        filename2 = wget.download(url2, out=d)
-        filename3 = wget.download(url_vocab, out=d)
-        if d == None:
-            d = ''
-        with zipfile.ZipFile(d+filename2, "r") as zip_ref:
-            zip_ref.extractall(d+filename2.replace('.zip', ''))
-        modelv = True
-    # Download files to use NeuralMind pre-model large
-    if model == 'neuralmindlarge':
-        url2 = 'https://neuralmind-ai.s3.us-east-2.amazonaws.com/nlp/bert-large-portuguese-cased/bert-large-portuguese-cased_pytorch_checkpoint.zip'
-        url_vocab = 'https://neuralmind-ai.s3.us-east-2.amazonaws.com/nlp/bert-large-portuguese-cased/vocab.txt'
-        filename2 = wget.download(url2, out=d)
-        filename3 = wget.download(url_vocab, out=d)
-        if d == None:
-            d = ''
-        with zipfile.ZipFile(d+filename2, "r") as zip_ref:
-            zip_ref.extractall(d+filename2.replace('.zip', ''))
-        modelv = True
-    # If don't download any model return false, else return true
-    return modelv