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test-fake_news_classification
Phoenyx83/test-fake_news_classification
test-fake_news_classification is a text classification model from Phoenyx83. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 1532855215 - CO2 Emissions (in grams): 34.1275
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Repo size
527 MB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Access
- Public
- Created
- Sep 22, 2022
- Updated
- Sep 22, 2022
- SHA
- 58cceb03
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 1532855215
- CO2 Emissions (in grams): 34.1275
Validation Metrics
- Loss: 0.000
- Accuracy: 1.000
- Precision: 1.000
- Recall: 1.000
- AUC: 1.000
- F1: 1.000
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 AutoTrain"}' https://api-inference.huggingface.co/models/Phoenyx83/autotrain-fake-news-classification-1532855215
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Phoenyx83/autotrain-fake-news-classification-1532855215", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Phoenyx83/autotrain-fake-news-classification-1532855215", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Languages
- en
- Created
- Sep 22, 2022
- Updated
- Sep 22, 2022