fix: dealing with unnecessary imports

NLPutils.py

@@ -9,9 +9,14 @@ import nltk
 import string
 from gensim.utils import simple_preprocess
 from nltk.corpus import stopwords
+from huggingface_hub import hf_hub_download
 
 def load_model():
-    return gensim.models.KeyedVectors.load_word2vec_format('./wiki.en.vec')
+    token = "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"
+    REPO_ID = "gonzalocordova/word2vec_fastText"
+    FILENAME = "wiki.en.vec"
+    model_pth = hf_hub_download(repo_id=REPO_ID, filename=FILENAME, repo_type="model", use_auth_token=token)
+    return gensim.models.KeyedVectors.load_word2vec_format(model_pth, binary=False)
 
 # Keywords for each defined topic
 topic_keywords = {

app.py

@@ -1,9 +1,4 @@
 import gradio as gr
-import numpy as np
-import torch
-import os
-from torchvision import transforms
-from huggingface_hub import hf_hub_download
 import NLPutils as nlp
 
 model = nlp.load_model()