app.py

from flask import Flask, jsonify, request
from transformers import AutoAdapterModel, AutoTokenizer, TextClassificationPipeline
from huggingface_hub import Repository

tokenizer = AutoTokenizer.from_pretrained("UBC-NLP/MARBERT", cache_dir="new_cache_dir/)
model = AutoAdapterModel.from_pretrained("UBC-NLP/MARBERT", cache_dir="new_cache_dir/)
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("aoc3_adapter", set_active=True, with_head=False)
model.load_adapter("aoc4_adapter", set_active=True, with_head=False)
model.load_adapter("sarcasm_adapter", set_active=True, with_head=False)

model.load_adapter_fusion("fusion_adapter/aoc(3),aoc(4),sarcasm",with_head=True, set_active=True)

pipe = TextClassificationPipeline(tokenizer=tokenizer, model=model)


app = Flask(__name__)

@app.route("/", methods=['GET'])
def home():
    return "<h1>GFG is great platform to learn</h1>"

if __name__ == "__main__":
  app.run()