Update app.py

app.py

@@ -1,22 +1,21 @@
 from flask import Flask, jsonify, request, render_template
 from transformers import AutoAdapterModel, AutoTokenizer, TextClassificationPipeline
-from huggingface_hub import Repository
 
-tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/MARBERT")
-model = AutoAdapterModel.from_pretrained("UBC-NLP/MARBERT")
+# tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/MARBERT")
+# model = AutoAdapterModel.from_pretrained("UBC-NLP/MARBERT")
 
 # sarcasm_adapter = Repository(local_dir="sarcasm_adapter", clone_from="nehalelkaref/sarcasm_adapter")
 # aoc3_adapter = Repository(local_dir="aoc3_adapter", clone_from="nehalelkaref/aoc3_adapter")
 # aoc4_adapter = Repository(local_dir="aoc4_adapter", clone_from="nehalelkaref/aoc4_adapter")
 # fusion_adapter = Repository(local_dir="fusion_adapter", clone_from="nehalelkaref/region_fusion")
 
-model.load_adapter("nehalelkaref/aoc3_adapter", set_active=True, with_head=False, source="hf")
-model.load_adapter("nehalelkaref/aoc4_adapter", set_active=True, with_head=False, source="hf")
-model.load_adapter("nehalelkaref/sarcasm_adapter", set_active=True, with_head=False, source="hf")
+# model.load_adapter("nehalelkaref/aoc3_adapter", set_active=True, with_head=False, source="hf")
+# model.load_adapter("nehalelkaref/aoc4_adapter", set_active=True, with_head=False, source="hf")
+# model.load_adapter("nehalelkaref/sarcasm_adapter", set_active=True, with_head=False, source="hf")
 
 # model.load_adapter_fusion("nehalelkaref/region_fusion",with_head=True, set_active=True, source="hf")
 
-pipe = TextClassificationPipeline(tokenizer=tokenizer, model=model)
+# pipe = TextClassificationPipeline(tokenizer=tokenizer, model=model)
 
 
 app = Flask(__name__)
@@ -25,5 +24,9 @@ app = Flask(__name__)
 def home():
     return render_template('home.html')
 
+@app.route('/classify', methods = ['POST'])
+def classify():
+    return "<h> text <\h>"
+
 if __name__ == "__main__":
   app.run()