negative positive
---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- sarahlmk/autonlp-data-imdb-classification
co2_eq_emissions: 274.81371614671764
---

# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 596216804
- CO2 Emissions (in grams): 274.81371614671764

## Validation Metrics

- Loss: 0.24049481749534607
- Accuracy: 0.9239
- Precision: 0.9143695014662757
- Recall: 0.9354
- AUC: 0.9781644
- F1: 0.9247652001977262

## 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 AutoNLP"}' https://api-inference.huggingface.co/models/sarahlmk/autonlp-imdb-classification-596216804
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("sarahlmk/autonlp-imdb-classification-596216804", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("sarahlmk/autonlp-imdb-classification-596216804", use_auth_token=True)

inputs = tokenizer("I love AutoNLP", return_tensors="pt")

outputs = model(**inputs)
```