nehalelkaref commited on
Commit
de4975e
1 Parent(s): fd5008e

Update main.py

Browse files
Files changed (1) hide show
  1. main.py +11 -11
main.py CHANGED
@@ -1,8 +1,8 @@
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- from flask import Flask, jsonify, request
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  from transformers import AutoAdapterModel, AutoTokenizer, TextClassificationPipeline
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  from huggingface_hub import Repository
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- app = Flask(__name__)
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  #define model
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  tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/MARBERT")
@@ -22,15 +22,15 @@ model.load_adapter_fusion("/fusion_adapter/aoc(3),aoc(4),sarcasm",with_head=True
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  pipe = TextClassificationPipeline(tokenizer=tokenizer, model=model)
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- @app.route('/predict', methods=['POST'])
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- def predict():
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- text = request.json['inputs']
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- prediction = pipe(text)
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- labels = {"LABEL_0":"GULF", "LABEL_1":"LEVANT","LABEL_2":"EGYPT"}
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- regions = []
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- for res in prediction:
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- regions.append(labels[res['label']])
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- return jsonify({'response': regions})
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+
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  from transformers import AutoAdapterModel, AutoTokenizer, TextClassificationPipeline
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  from huggingface_hub import Repository
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+ # app = Flask(__name__)
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  #define model
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  tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/MARBERT")
 
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  pipe = TextClassificationPipeline(tokenizer=tokenizer, model=model)
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+ # @app.route('/predict', methods=['POST'])
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+ # def predict():
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+ # text = request.json['inputs']
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+ # prediction = pipe(text)
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+ # labels = {"LABEL_0":"GULF", "LABEL_1":"LEVANT","LABEL_2":"EGYPT"}
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+ # regions = []
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+ # for res in prediction:
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+ # regions.append(labels[res['label']])
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+ # return jsonify({'response': regions})
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