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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-regression
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+ language:
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+ - es
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+ widget:
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+ - text: "I love AutoTrain 🤗"
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+ datasets:
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+ - tizan25/autotrain-data-twitter-currency-regression
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+ co2_eq_emissions:
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+ emissions: 5.819688265631011
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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: Single Column Regression
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+ - Model ID: 3698798560
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+ - CO2 Emissions (in grams): 5.8197
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+
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+ ## Validation Metrics
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+
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+ - Loss: 7.583
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+ - MSE: 7.583
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+ - MAE: 1.332
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+ - R2: 0.005
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+ - RMSE: 2.754
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+ - Explained Variance: 0.005
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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/tizan25/autotrain-twitter-currency-regression-3698798560
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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("tizan25/autotrain-twitter-currency-regression-3698798560", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("tizan25/autotrain-twitter-currency-regression-3698798560", 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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+ "problem_type": "regression",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.25.1",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ }
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