# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("luisu0124/Amazon_review")
model = AutoModelForSequenceClassification.from_pretrained("luisu0124/Amazon_review")Quick Links
language:
- es
tags:
- amazon_reviews_multi
- Text Clasiffication
Dataset
Example structure review:
| review_id (string) | product_id (string) | reviewer_id (string) | stars (int) | review_body (string) | review_title (string) | language (string) | product_category (string) |
|---|---|---|---|---|---|---|---|
| de_0203609 | product_de_0865382 | reviewer_de_0267719 | 1 | Armband ist leider nach 1 Jahr kaputt gegangen | Leider nach 1 Jahr kaputt | de | sports |
Model
Model train
| Text | Classification |
|---|---|
| review_body | stars |
Model test
Clasiffication reviews in Spanish
Uses POS, NEG labels.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="luisu0124/Amazon_review")