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rumor
tristantristantristan/rumor
rumor is a text classification model from tristantristantristan. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 813825547 - CO2 Emissions (in grams): 0.056186258092819436
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- May 2, 2022
- Updated
- May 2, 2022
- SHA
- c0be943d
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 813825547
- CO2 Emissions (in grams): 0.056186258092819436
Validation Metrics
- Loss: 0.15057753026485443
- Accuracy: 0.9738805970149254
- Precision: 0.9469026548672567
- Recall: 0.9304347826086956
- AUC: 0.9891149437157905
- F1: 0.9385964912280702
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/tristantristantristan/autotrain-rumour_detection-813825547
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("tristantristantristan/autotrain-rumour_detection-813825547", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("tristantristantristan/autotrain-rumour_detection-813825547", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- May 2, 2022
- Updated
- May 2, 2022