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Commit From AutoTrain

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.gitattributes CHANGED
@@ -32,3 +32,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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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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+ - unk
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+ widget:
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+ - text: "I love AutoTrain 🤗"
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+ datasets:
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+ - hr-elrond/autotrain-data-p2_finbert_training_100
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+ co2_eq_emissions:
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+ emissions: 0.2967273355715001
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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: Binary Classification
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+ - Model ID: 56875131853
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+ - CO2 Emissions (in grams): 0.2967
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+
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+ ## Validation Metrics
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+
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+ - Loss: 0.068
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+ - Accuracy: 0.984
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+ - Precision: 0.993
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+ - Recall: 0.983
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+ - AUC: 0.996
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+ - F1: 0.988
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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/hr-elrond/autotrain-p2_finbert_training_100-56875131853
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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("hr-elrond/autotrain-p2_finbert_training_100-56875131853", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("hr-elrond/autotrain-p2_finbert_training_100-56875131853", 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": "4.28.1",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ }
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