# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("CouchCat/ma_mlc_v7_distil")
model = AutoModelForSequenceClassification.from_pretrained("CouchCat/ma_mlc_v7_distil", device_map="auto")Quick Links
Description
A Multi-label text classification model trained on a customer feedback data using DistilBert. Possible labels are:
- Delivery (delivery status, time of arrival, etc.)
- Return (return confirmation, return label requests, etc.)
- Product (quality, complaint, etc.)
- Monetary (pending transactions, refund, etc.)
Usage
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("CouchCat/ma_mlc_v7_distil")
model = AutoModelForSequenceClassification.from_pretrained("CouchCat/ma_mlc_v7_distil")
- Downloads last month
- 12
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CouchCat/ma_mlc_v7_distil")