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Commit From AutoTrain

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.gitattributes CHANGED
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README.md ADDED
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+ ---
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+ tags:
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+ - autotrain
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+ - text-classification
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+ language:
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+ - it
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+ widget:
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+ - text: "I love AutoTrain 🤗"
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+ datasets:
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+ - tradicio/autotrain-data-it-emotion-analysis
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+ co2_eq_emissions:
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+ emissions: 0.4489187526120041
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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: 43095109829
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+ - CO2 Emissions (in grams): 0.4489
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.566
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+ - Accuracy: 0.828
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+ - Macro F1: 0.828
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+ - Micro F1: 0.828
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+ - Weighted F1: 0.828
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+ - Macro Precision: 0.828
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+ - Micro Precision: 0.828
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+ - Weighted Precision: 0.828
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+ - Macro Recall: 0.828
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+ - Micro Recall: 0.828
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+ - Weighted Recall: 0.828
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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/tradicio/autotrain-it-emotion-analysis-43095109829
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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("tradicio/autotrain-it-emotion-analysis-43095109829", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("tradicio/autotrain-it-emotion-analysis-43095109829", 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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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.25.1",
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+ "use_cache": true,
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+ }
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