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Priv-Consent
Adi2K/Priv-Consent
Priv-Consent is a text classification model from Adi2K. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 12592372
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Repo size
876 MB
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1
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Repo makeup
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Sep 24, 2021
- SHA
- f14517d9
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Datasets
Model card
From the Hugging Face model README
Model
- Problem type: Binary Classification
- Model ID: 12592372
Validation Metrics
- Loss: 0.23033875226974487
- Accuracy: 0.9138655462184874
- Precision: 0.9087136929460581
- Recall: 0.9201680672268907
- AUC: 0.9690346726926065
- F1: 0.9144050104384133
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/Adi2K/autonlp-Priv-Consent-12592372
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Adi2K/autonlp-Priv-Consent-12592372", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Adi2K/autonlp-Priv-Consent-12592372", use_auth_token=True)
inputs = tokenizer("I love AutoNLP", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- eng
- Created
- Mar 2, 2022
- Updated
- Sep 24, 2021