canahmet-29 commited on
Commit
b5a9227
1 Parent(s): 095c070

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +7 -4
app.py CHANGED
@@ -60,20 +60,23 @@ elif input_method == "Dosya Yükle":
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  input_text = ""
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  @st.cache_resource
 
 
 
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  def load_pipeline(model_name, task_type):
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- if task_type == "Metin Sınıflandırma":
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  model = AutoModelForSequenceClassification.from_pretrained(model_name)
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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  return pipeline('text-classification', model=model, tokenizer=tokenizer)
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- elif task_type == "Metin Analizi":
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  model = AutoModelForTokenClassification.from_pretrained(model_name)
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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  return pipeline('ner', model=model, tokenizer=tokenizer)
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- elif task_type == "Duygu Analizi":
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  model = AutoModelForSequenceClassification.from_pretrained(model_name)
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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  return pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)
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- elif task_type == "Metin Oluşturma":
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  model = AutoModelWithLMHead.from_pretrained(model_name)
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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  return pipeline('text-generation', model=model, tokenizer=tokenizer)
 
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  input_text = ""
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  @st.cache_resource
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+ task = st.sidebar.selectbox("Görev Seç", ['Metin Sınıflandırma', 'Metin Analizi', 'Duygu Analizi', 'Metin Oluşturma'])
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+
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+
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  def load_pipeline(model_name, task_type):
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+ if task == "Metin Sınıflandırma":
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  model = AutoModelForSequenceClassification.from_pretrained(model_name)
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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  return pipeline('text-classification', model=model, tokenizer=tokenizer)
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+ elif task == "Metin Analizi":
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  model = AutoModelForTokenClassification.from_pretrained(model_name)
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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  return pipeline('ner', model=model, tokenizer=tokenizer)
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+ elif task == "Duygu Analizi":
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  model = AutoModelForSequenceClassification.from_pretrained(model_name)
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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  return pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)
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+ elif task == "Metin Oluşturma":
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  model = AutoModelWithLMHead.from_pretrained(model_name)
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  tokenizer = AutoTokenizer.from_pretrained(model_name)
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  return pipeline('text-generation', model=model, tokenizer=tokenizer)