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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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- testing/autonlp-data-ingredient_sentiment_analysis |
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co2_eq_emissions: 1.8458289701133035 |
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--- |
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# Model Trained Using AutoNLP |
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- Problem type: Entity Extraction |
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- Model ID: 19126711 |
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- CO2 Emissions (in grams): 1.8458289701133035 |
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## Validation Metrics |
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- Loss: 0.054593171924352646 |
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- Accuracy: 0.9790668170284748 |
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- Precision: 0.8029411764705883 |
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- Recall: 0.6026490066225165 |
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- F1: 0.6885245901639344 |
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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/testing/autonlp-ingredient_sentiment_analysis-19126711 |
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``` |
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Or Python API: |
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``` |
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from transformers import AutoModelForTokenClassification, AutoTokenizer |
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model = AutoModelForTokenClassification.from_pretrained("testing/autonlp-ingredient_sentiment_analysis-19126711", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("testing/autonlp-ingredient_sentiment_analysis-19126711", 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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``` |
