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--- |
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tags: autotrain |
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language: unk |
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widget: |
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- text: "I love AutoTrain 🤗" |
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datasets: |
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- ScarlettSun9/autotrain-data-ZuoZhuan |
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co2_eq_emissions: 8.343592303925112 |
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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: 1100540141 |
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- CO2 Emissions (in grams): 8.343592303925112 |
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## Validation Metrics |
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- Loss: 0.38094884157180786 |
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- Accuracy: 0.8795777325860159 |
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- Precision: 0.8171375141922127 |
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- Recall: 0.8417033571821684 |
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- F1: 0.8292385373953709 |
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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/ScarlettSun9/autotrain-ZuoZhuan-1100540141 |
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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("ScarlettSun9/autotrain-ZuoZhuan-1100540141", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("ScarlettSun9/autotrain-ZuoZhuan-1100540141", 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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``` |
