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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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- Jeska/autonlp-data-vaccinfaq |
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co2_eq_emissions: 27.135492487925884 |
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--- |
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# Model Trained Using AutoNLP |
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- Problem type: Multi-class Classification |
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- Model ID: 22144706 |
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- CO2 Emissions (in grams): 27.135492487925884 |
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## Validation Metrics |
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- Loss: 1.81697416305542 |
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- Accuracy: 0.6377269139700079 |
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- Macro F1: 0.5181293370145044 |
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- Micro F1: 0.6377269139700079 |
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- Weighted F1: 0.631117826235572 |
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- Macro Precision: 0.5371452512845428 |
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- Micro Precision: 0.6377269139700079 |
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- Weighted Precision: 0.6655055695465463 |
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- Macro Recall: 0.5609328178925124 |
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- Micro Recall: 0.6377269139700079 |
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- Weighted Recall: 0.6377269139700079 |
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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/Jeska/autonlp-vaccinfaq-22144706 |
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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("Jeska/autonlp-vaccinfaq-22144706", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("Jeska/autonlp-vaccinfaq-22144706", 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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``` |
