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autotrain-Fake-word-detection-894729103
hidude562/autotrain-Fake-word-detection-894729103
autotrain-Fake-word-detection-894729103 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: 894729103 - CO2 Emissions (in grams): 78.6804326698628
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Repo size
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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
- a0ed8c8e
Try a prompt
Model card
From the Hugging Face model README
Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 894729103
- CO2 Emissions (in grams): 78.6804326698628
Validation Metrics
- Loss: 0.19282743334770203
- Accuracy: 0.953471162295916
- Precision: 0.9971258014592085
- Recall: 0.902
- AUC: 0.9779055158764306
- F1: 0.9471805103433791
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-894729103
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("hidude562/autotrain-Fake-word-detection-894729103", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("hidude562/autotrain-Fake-word-detection-894729103", 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