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Tarive
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Test1

Text Classification
Transformers
PyTorch
Enawené-Nawé
bert
Trained with AutoTrain
text-embeddings-inference
Model card Files
xet
 Community
How to use from the
Use from the
Transformers library
# Gated model: Login with a HF token with gated access permission
hf auth login
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="Tarive/Test1")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("Tarive/Test1")
model = AutoModelForSequenceClassification.from_pretrained("Tarive/Test1")
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Model Trained Using AutoTrain

  • Problem type: Text Classification
  • CO2 Emissions (in grams): 0.0000

Validation Metrics

loss: 0.688549816608429

f1: 0.7096774193548387

precision: 0.55

recall: 1.0

auc: 0.45075757575757575

accuracy: 0.55

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