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--- |
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tags: autonlp |
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language: en |
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widget: |
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- text: "I love AutoNLP 🤗" |
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datasets: |
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- sefaozalpadl/autonlp-data-election_relevancy_analysis |
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co2_eq_emissions: 1.3248523193990855 |
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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: 23315155 |
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- CO2 Emissions (in grams): 1.3248523193990855 |
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## Validation Metrics |
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- Loss: 0.4240806996822357 |
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- Accuracy: 0.8173913043478261 |
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- Precision: 0.8837209302325582 |
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- Recall: 0.8085106382978723 |
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- AUC: 0.8882580285281696 |
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- F1: 0.8444444444444444 |
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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/sefaozalpadl/autonlp-election_relevancy_analysis-23315155 |
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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("sefaozalpadl/autonlp-election_relevancy_analysis-23315155", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("sefaozalpadl/autonlp-election_relevancy_analysis-23315155", 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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``` |
