Commit From AutoTrain

.gitattributes

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README.md

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+---
+tags:
+- autotrain
+- text-classification
+language:
+- en
+widget:
+- text: "I love AutoTrain 🤗"
+datasets:
+- hoshingakag/autotrain-data-emotion-detection
+co2_eq_emissions:
+  emissions: 2.3491292126039087
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Multi-class Classification
+- Model ID: 1587956110
+- CO2 Emissions (in grams): 2.3491
+
+## Validation Metrics
+
+- Loss: 0.448
+- Accuracy: 0.888
+- Macro F1: 0.823
+- Micro F1: 0.888
+- Weighted F1: 0.884
+- Macro Precision: 0.885
+- Micro Precision: 0.888
+- Weighted Precision: 0.890
+- Macro Recall: 0.800
+- Micro Recall: 0.888
+- Weighted Recall: 0.888
+
+
+## Usage
+
+You can use cURL to access this model:
+
+```
+$ 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/hoshingakag/autotrain-emotion-detection-1587956110
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("hoshingakag/autotrain-emotion-detection-1587956110", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("hoshingakag/autotrain-emotion-detection-1587956110", use_auth_token=True)
+
+inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+
+outputs = model(**inputs)
+```

config.json

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