File size: 4,432 Bytes
70e373f 56890f7 70e373f 59e7461 70e373f 1d56a59 22e609f c8c34b0 70e373f 657d5be ad67ce6 70e373f ad67ce6 70e373f ad67ce6 70e373f 29128dc 1d56a59 70e373f 22e609f d298949 498763b c53d81e d298949 70e373f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
from transformers import AutoModelForSequenceClassification
from transformers import AutoTokenizer, AutoConfig
from clean_data import cleaned_complaints
import numpy as np
from scipy.special import softmax
import gradio as gr
# Preprocess text (username and link placeholders)
def preprocess(text):
new_text = []
for t in text.split(" "):
t = '@user' if t.startswith('@') and len(t) > 1 else t
t = 'http' if t.startswith('http') else t
new_text.append(t)
return " ".join(new_text)
# load model
MODEL = f"ThirdEyeData/Consumer-Complaint-Segmentation"
model = AutoModelForSequenceClassification.from_pretrained(MODEL)
#model.save_pretrained(MODEL)
tokenizer = AutoTokenizer.from_pretrained(MODEL)
config = AutoConfig.from_pretrained(MODEL)
# create classifier function
def classify_compliant(text):
text = cleaned_complaints(text)
text = preprocess(text)
encoded_input = tokenizer(text, return_tensors='pt')
output = model(**encoded_input)
scores = output[0][0].detach().numpy()
scores = softmax(scores)
# Print labels and scores
probs = {}
ranking = np.argsort(scores)
ranking = ranking[::-1]
l = config.id2label[ranking[0]]
#s = scores[ranking[i]]
#probs[l] = np.round(float(s), 4)
return l
#build the Gradio app
#Instructuction = "Write an imaginary review about a product or service you might be interested in."
title="Consumer Complaint Segmentation"
description = """Write a complaint insurance product or service,\
see how the machine learning model is able to predict your Complaint type"""
article = """
- Click submit button to test Consumer Complaint Segmentation
- Click clear button to refresh text
"""
gr.Interface(classify_compliant,
'text',
'label',
title = title,
description = description,
#Instruction = Instructuction,
article = article,
allow_flagging = "never",
live = False,
examples=["""Debt to XXXX was satisfied when account was closed and all equipment was returned, XXXX 2014. NO further contact from XXXX XXXX, however,
13 months later this " collection \'\' shows up on on my credit report. NO prior written or phone communication.
I have attempted to contact this Debt Collector and can not get any information pertaining to my account from the""",
"""I receive repeated calls daily from this company. I signed up for a debt consolidation service and they continued to call my personal phone and my place of employment. \nCausing a phone to ring repeatedly in the attempts to annoy or establish communication is against the law.
I have asked for the calls to stop and sent a cease and desist and still the calls continue""",
"""I was erroneously reported to all three major credit Bureaus by XXXX for a professional fee I paid for {$220.00} on XX/XX/2015.
I have the cancelled check. This check cleared the bank on XX/XX/2015.
I receivePlease note-I have the recorded call on file and it was disclosed to the company that I was recording.
I called Hunter Warfield to come to a resoluation on some lease break fees I had with an apartment complex called XXXX XXXX.
The representative told me the total amount due was {$2100.00} and that I can settle for half of that amount. Unfortunately, I was unable to accept the settlement but began to question the amount because my last statement was {$1800.00} and there was nothing written in the contract for additional interest charges should my account go into collection. I told the representative that I will pay the amount actually owed and I want to make a payment arrangement. She told me I ca n\'t just do what I want, If I want to pay the original amount due, it has to be paid in full. I told her that that is not fair debt collection practice and that I am only contractually obligated to the {$1800.00} and we can set up an arrangement from that.
She asked me in a condensing told """ ,
"""ERC is the company, first they say, I owe for this debt that I have no idea or clue what it is or if I even did it.
then the debt is about 8 years old, and also threaten take me to court if I don't pay"""
]
).launch()
|