cleaned up

app.py

@@ -1,47 +1,19 @@
 import datetime
 import gradio as gr
 from huggingface_hub import hf_hub_download
-from langdetect import detect, DetectorFactory, detect_langs
-import fasttext
 from transformers import pipeline
 
 models = {
-          'en': 'Narsil/deberta-large-mnli-zero-cls', #'facebook/bart-large-mnli', # English
-          #'es': 'Recognai/zeroshot_selectra_medium', # Spanish
-          #'it': 'joeddav/xlm-roberta-large-xnli', # Italian
-          #'ru': 'DeepPavlov/xlm-roberta-large-en-ru-mnli', # Russian
-          #'tr': 'vicgalle/xlm-roberta-large-xnli-anli', # Turkish
-          #'no': 'NbAiLab/nb-bert-base-mnli', # Norsk
-          #'de': 'Sahajtomar/German_Zeroshot' # German
-          }
+          'en': 'Narsil/deberta-large-mnli-zero-cls'
+         }
 
 hypothesis_templates = {
-                        'en': 'This example is {}.', # English
-                        #'es': 'Este ejemplo es {}.', # Spanish
-                        #'it': 'Questo esempio è {}.', # Italian
-                        #'ru': 'Этот пример {}.', # Russian
-                        #'tr': 'Bu örnek {}.', # Turkish
-                        #'no': 'Dette eksempelet er {}.', # Norsk
-                        #'de': 'Dieses beispiel ist {}.' # German
-                        }
+                        'en': 'This example is {}.'
+                       }
 
 classifiers = {'en': pipeline("zero-shot-classification", hypothesis_template=hypothesis_templates['en'],
-                              model=models['en']),
-               #'es': pipeline("zero-shot-classification", hypothesis_template=hypothesis_templates['es'],
-               #               model=models['es']),
-               #'it': pipeline("zero-shot-classification", hypothesis_template=hypothesis_templates['it'],
-               #               model=models['it']),
-               #'ru': pipeline("zero-shot-classification", hypothesis_template=hypothesis_templates['ru'],
-               #               model=models['ru']),
-               #'tr': pipeline("zero-shot-classification", hypothesis_template=hypothesis_templates['tr'],
-               #               model=models['tr']),
-               #'no': pipeline("zero-shot-classification", hypothesis_template=hypothesis_templates['no'],
-               #               model=models['no']),
-               #'de': pipeline("zero-shot-classification", hypothesis_template=hypothesis_templates['de'],
-               #               model=models['de'])
-               }
-
-fasttext_model = fasttext.load_model(hf_hub_download("julien-c/fasttext-language-id", "lid.176.bin"))
+                              model=models['en'])
+              }
 
 def prep_examples():
     example_text1 = "The tangy feel in my mouth was a different experience altogether."
@@ -211,7 +183,6 @@ iface = gr.Interface(
         gr.inputs.Radio(choices=[False, True],
         label="Multi-label?")],
     outputs=gr.outputs.Label(),
-    #interpretation="default",
     examples=prep_examples())
 
 iface.launch()

requirements.txt

@@ -1,6 +1,3 @@
 transformers
-sentence-transformers
 torch
-langdetect
-fasttext