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---
language: unk
datasets:
- anwesham/autotrain-data-imdb-sentiment-analysis
co2_eq_emissions: 0.2033402242358345
---
- Problem type: Binary Classification
- Model ID: 864927559
- CO2 Emissions (in grams): 0.2033402242358345
## Validation Metrics
- Loss: 0.18383920192718506
- Accuracy: 0.9318
- Precision: 0.9560625264047318
- Recall: 0.9052
- AUC: 0.98281574
- F1: 0.9299363057324841
## 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/anwesham/autotrain-imdb-sentiment-analysis-864927559
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("anwesham/autotrain-imdb-sentiment-analysis-864927559", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("anwesham/autotrain-imdb-sentiment-analysis-864927559", use_auth_token=True)
inputs = tokenizer("I love to eat food", return_tensors="pt")
outputs = model(**inputs)
``` |