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--- |
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tags: autotrain |
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language: en |
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widget: |
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- text: "I love AutoTrain 🤗" |
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datasets: |
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- Shenzy2/autotrain-data-NER4DesignTutor |
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co2_eq_emissions: 0.004032656988228696 |
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--- |
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# Model Trained Using AutoTrain |
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- Problem type: Entity Extraction |
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- Model ID: 1169643336 |
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- CO2 Emissions (in grams): 0.004032656988228696 |
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## Validation Metrics |
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- Loss: 0.677674412727356 |
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- Accuracy: 0.8129095674967235 |
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- Precision: 0.4424778761061947 |
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- Recall: 0.4844961240310077 |
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- F1: 0.4625346901017577 |
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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 AutoTrain"}' https://api-inference.huggingface.co/models/Shenzy2/autotrain-NER4DesignTutor-1169643336 |
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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("Shenzy2/autotrain-NER4DesignTutor-1169643336", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("Shenzy2/autotrain-NER4DesignTutor-1169643336", use_auth_token=True) |
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inputs = tokenizer("I love AutoTrain", return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
