neg pos
---
tags: autonlp
language: en
widget:
- text: "I love AutoNLP 🤗"
datasets:
- chiragme/autonlp-data-imdb-sentiment-analysis
co2_eq_emissions: 147.38973865706626
---

# Model Trained Using AutoNLP

- Problem type: Binary Classification
- Model ID: 623817873
- CO2 Emissions (in grams): 147.38973865706626

## Validation Metrics

- Loss: 0.2412157654762268
- Accuracy: 0.9306
- Precision: 0.9377795851972347
- Recall: 0.9224
- AUC: 0.97000504
- F1: 0.9300262149626941

## 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/chiragme/autonlp-imdb-sentiment-analysis-623817873
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("chiragme/autonlp-imdb-sentiment-analysis-623817873", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("chiragme/autonlp-imdb-sentiment-analysis-623817873", use_auth_token=True)

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

outputs = model(**inputs)
```