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Model Trained Using AutoTrain

  • Problem type: Entity Extraction
  • Model ID: 69856137957
  • CO2 Emissions (in grams): 0.1165

Validation Metrics

  • Loss: 1.510
  • Accuracy: 0.706
  • Precision: 0.648
  • Recall: 0.679
  • F1: 0.663

Usage

You can use cURL to access this model:

$ 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/davanstrien/autotrain-french-ner-blank-model-69856137957

Or Python API:

from transformers import AutoModelForTokenClassification, AutoTokenizer

model = AutoModelForTokenClassification.from_pretrained("davanstrien/autotrain-french-ner-blank-model-69856137957", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("davanstrien/autotrain-french-ner-blank-model-69856137957", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)
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Model size
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I64
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F32
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Inference Examples
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Dataset used to train davanstrien/CamemBERT-MedNERF