README.md

---
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: "I love AutoTrain"
datasets:
- maxzancanaro/autotrain-data-l_liability_484
co2_eq_emissions:
  emissions: 0.020054143263839096
---

# Model Trained Using AutoTrain

- Problem type: Binary Classification
- Model ID: 95277146331
- CO2 Emissions (in grams): 0.0201

## Validation Metrics

- Loss: 0.115
- Accuracy: 0.959
- Precision: 0.980
- Recall: 0.941
- AUC: 0.995
- F1: 0.960

## 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/maxzancanaro/autotrain-l_liability_484-95277146331
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("maxzancanaro/autotrain-l_liability_484-95277146331", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("maxzancanaro/autotrain-l_liability_484-95277146331", use_auth_token=True)

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

outputs = model(**inputs)
```