---
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: "I love AutoTrain"
datasets:
- GRPUI/autotrain-data-ssugt-model
co2_eq_emissions:
  emissions: 0.01609460864740505
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 91334144491
- CO2 Emissions (in grams): 0.0161

## Validation Metrics

- Loss: 0.022
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000


## 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/GRPUI/autotrain-ssugt-model-91334144491
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("GRPUI/autotrain-ssugt-model-91334144491", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("GRPUI/autotrain-ssugt-model-91334144491", use_auth_token=True)

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

outputs = model(**inputs)
```