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:
+- bvint/autotrain-data-sphere-lecture-demo
+co2_eq_emissions:
+  emissions: 0.004735324111068996
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Multi-class Classification
+- Model ID: 1671659193
+- CO2 Emissions (in grams): 0.0047
+
+## Validation Metrics
+
+- Loss: 0.803
+- Accuracy: 0.658
+- Macro F1: 0.478
+- Micro F1: 0.658
+- Weighted F1: 0.580
+- Macro Precision: 0.424
+- Micro Precision: 0.658
+- Weighted Precision: 0.520
+- Macro Recall: 0.549
+- Micro Recall: 0.658
+- Weighted Recall: 0.658
+
+
+## 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/bvint/autotrain-sphere-lecture-demo-1671659193
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("bvint/autotrain-sphere-lecture-demo-1671659193", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("bvint/autotrain-sphere-lecture-demo-1671659193", use_auth_token=True)
+
+inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+
+outputs = model(**inputs)
+```

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