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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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- unk |
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widget: |
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- text: "I love AutoTrain 🤗" |
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datasets: |
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- huynhdoo/autotrain-data-ell-conventions |
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co2_eq_emissions: |
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emissions: 2.6341173422087247 |
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--- |
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# Model Trained Using AutoTrain |
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- Problem type: Single Column Regression |
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- Model ID: 2218371153 |
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- CO2 Emissions (in grams): 2.6341 |
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## Validation Metrics |
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- Loss: 0.259 |
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- MSE: 0.259 |
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- MAE: 0.402 |
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- R2: 0.426 |
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- RMSE: 0.509 |
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- Explained Variance: 0.439 |
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## Usage |
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You can use cURL to access this model: |
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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/huynhdoo/autotrain-ell-conventions-2218371153 |
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``` |
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Or Python API: |
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``` |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model = AutoModelForSequenceClassification.from_pretrained("huynhdoo/autotrain-ell-conventions-2218371153", use_auth_token=True) |
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tokenizer = AutoTokenizer.from_pretrained("huynhdoo/autotrain-ell-conventions-2218371153", use_auth_token=True) |
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inputs = tokenizer("I love AutoTrain", return_tensors="pt") |
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outputs = model(**inputs) |
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``` |
