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yelp-rating-classification
nihaldsouza1/yelp-rating-classification
yelp-rating-classification is a text classification model from nihaldsouza1. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Multi-class Classification - Model ID: 545015430 - CO2 Emissions (in grams): 15.62335109262394
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Nov 3, 2022
- SHA
- 90dcbf4a
Try a prompt
Model card
From the Hugging Face model README
Custom-trained user model
- Problem type: Multi-class Classification
- Model ID: 545015430
- CO2 Emissions (in grams): 15.62335109262394
Validation Metrics
- Loss: 0.7870086431503296
- Accuracy: 0.6631428571428571
- Macro F1: 0.6613073053700258
- Micro F1: 0.6631428571428571
- Weighted F1: 0.661157273964887
- Macro Precision: 0.6626911151999393
- Micro Precision: 0.6631428571428571
- Weighted Precision: 0.662191421927851
- Macro Recall: 0.6629735627465572
- Micro Recall: 0.6631428571428571
- Weighted Recall: 0.6631428571428571
Usage
You can use cURL to access this model:
$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoNLP"}' https://api-inference.huggingface.co/models/nihaldsouza1/autonlp-yelp-rating-classification-545015430
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("nihaldsouza1/autonlp-yelp-rating-classification-545015430", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("nihaldsouza1/autonlp-yelp-rating-classification-545015430", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Nov 3, 2022