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--- |
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tags: autonlp |
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language: unk |
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widget: |
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- text: "I love AutoNLP 🤗" |
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datasets: |
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- Qinghui/autonlp-data-fake-covid-news |
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co2_eq_emissions: 23.42719853096565 |
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--- |
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# Model Trained Using AutoNLP |
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- Problem type: Binary Classification |
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- Model ID: 36769078 |
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- CO2 Emissions (in grams): 23.42719853096565 |
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## Validation Metrics |
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- Loss: 0.15959647297859192 |
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- Accuracy: 0.9817757009345794 |
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- Precision: 0.980411361410382 |
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- Recall: 0.9813725490196078 |
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- AUC: 0.9982379201680672 |
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- F1: 0.9808917197452229 |
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## Usage |
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You can use cURL to access this model: |
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``` |
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$ 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/Qinghui/autonlp-fake-covid-news-36769078 |
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``` |
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Or Python API: |
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``` |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model = AutoModelForSequenceClassification.from_pretrained("Qinghui/autonlp-fake-covid-news-36769078", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("Qinghui/autonlp-fake-covid-news-36769078", use_auth_token=True) |
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inputs = tokenizer("I love AutoNLP", return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
