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Commit From AutoTrain

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README.md ADDED
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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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+ - EXOP/autotrain-data-exop-msc-flat-categories-multilingual
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+ co2_eq_emissions: 652.3729662301374
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+ ---
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+
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+ # Model Trained Using AutoTrain
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+
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+ - Problem type: Multi-class Classification
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+ - Model ID: 1147942216
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+ - CO2 Emissions (in grams): 652.3729662301374
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.4508252441883087
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+ - Accuracy: 0.8882102517882141
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+ - Macro F1: 0.7681095738330185
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+ - Micro F1: 0.8882102517882141
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+ - Weighted F1: 0.8873062298114072
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+ - Macro Precision: 0.8125021386404774
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+ - Micro Precision: 0.8882102517882141
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+ - Weighted Precision: 0.8875709606885154
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+ - Macro Recall: 0.7429489567097202
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+ - Micro Recall: 0.8882102517882141
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+ - Weighted Recall: 0.8882102517882141
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+
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+
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+ ## Usage
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+
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+ You can use cURL to access this model:
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+
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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/EXOP/autotrain-exop-msc-flat-categories-multilingual-1147942216
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+ ```
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+
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+ Or Python API:
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+
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+ ```
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+ from transformers import AutoModelForSequenceClassification, AutoTokenizer
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+
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+ model = AutoModelForSequenceClassification.from_pretrained("EXOP/autotrain-exop-msc-flat-categories-multilingual-1147942216", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("EXOP/autotrain-exop-msc-flat-categories-multilingual-1147942216", use_auth_token=True)
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+
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+ inputs = tokenizer("I love AutoTrain", return_tensors="pt")
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+
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+ outputs = model(**inputs)
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+ ```
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