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---
tags:
- autotrain
- text-classification
language:
- en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- Kaludi/autotrain-data-reviews-sentiment-analysis
co2_eq_emissions:
emissions: 24.76716845191504
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 3125888400
- CO2 Emissions (in grams): 24.7672
## Validation Metrics
- Loss: 0.159
- Accuracy: 0.952
- Precision: 0.965
- Recall: 0.938
- AUC: 0.988
- F1: 0.951
## 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/Kaludi/autotrain-reviews-sentiment-analysis-3125888400
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("Kaludi/autotrain-reviews-sentiment-analysis-3125888400", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("Kaludi/autotrain-reviews-sentiment-analysis-3125888400", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
``` |