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autotrain-Fake-word-detection-894729105
hidude562/autotrain-Fake-word-detection-894729105
autotrain-Fake-word-detection-894729105 is a text classification model from hidude562. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Binary Classification - Model ID: 894729105 - CO2 Emissions (in grams): 0.33855954604658545
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Repo size
1.3 GB
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.bin1.3 GB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- May 22, 2022
- Updated
- May 22, 2022
- SHA
- 47a55423
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 894729105
- CO2 Emissions (in grams): 0.33855954604658545
Validation Metrics
- Loss: 0.1247355192899704
- Accuracy: 0.970907913602516
- Precision: 0.9491899146774039
- Recall: 0.9901
- AUC: 0.9713629248773773
- F1: 0.969213450149283
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/hidude562/autotrain-Fake-word-detection-894729105
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("hidude562/autotrain-Fake-word-detection-894729105", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("hidude562/autotrain-Fake-word-detection-894729105", 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 22, 2022
- Updated
- May 22, 2022