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:
+- sabhashanki/autotrain-data-topic-prediction-latest
+co2_eq_emissions:
+  emissions: 2.8092927891228863
+---
+
+# Model Trained Using AutoTrain
+
+- Problem type: Multi-class Classification
+- Model ID: 2396974951
+- CO2 Emissions (in grams): 2.8093
+
+## Validation Metrics
+
+- Loss: 0.635
+- Accuracy: 0.840
+- Macro F1: 0.834
+- Micro F1: 0.840
+- Weighted F1: 0.837
+- Macro Precision: 0.839
+- Micro Precision: 0.840
+- Weighted Precision: 0.840
+- Macro Recall: 0.836
+- Micro Recall: 0.840
+- Weighted Recall: 0.840
+
+
+## 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/sabhashanki/autotrain-topic-prediction-latest-2396974951
+```
+
+Or Python API:
+
+```
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model = AutoModelForSequenceClassification.from_pretrained("sabhashanki/autotrain-topic-prediction-latest-2396974951", use_auth_token=True)
+
+tokenizer = AutoTokenizer.from_pretrained("sabhashanki/autotrain-topic-prediction-latest-2396974951", use_auth_token=True)
+
+inputs = tokenizer("I love AutoTrain", return_tensors="pt")
+
+outputs = model(**inputs)
+```

config.json

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vocab.json

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