Commit From AutoTrain

.gitattributes

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README.md

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+---
+tags:
+- autotrain
+- text-classification
+language:
+- unk
+widget:
+- text: "I love AutoTrain 🤗"
+datasets:
+- lewtun/autotrain-data-sphere-banking77
+co2_eq_emissions:
+  emissions: 0.040322592546588654
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Multi-class Classification
+- Model ID: 1565555714
+- CO2 Emissions (in grams): 0.0403
+
+## Validation Metrics
+
+- Loss: 0.317
+- Accuracy: 0.919
+- Macro F1: 0.920
+- Micro F1: 0.919
+- Weighted F1: 0.920
+- Macro Precision: 0.925
+- Micro Precision: 0.919
+- Weighted Precision: 0.923
+- Macro Recall: 0.919
+- Micro Recall: 0.919
+- Weighted Recall: 0.919
+
+
+## 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/lewtun/autotrain-sphere-banking77-1565555714
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("lewtun/autotrain-sphere-banking77-1565555714", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("lewtun/autotrain-sphere-banking77-1565555714", use_auth_token=True)
+
+inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+
+outputs = model(**inputs)
+```

config.json

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pytorch_model.bin

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tokenizer_config.json

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