Company Job Name OOV Zip
---
tags: autotrain
language: en
widget:
- text: "I love AutoTrain 🤗"
datasets:
- lucifermorninstar011/autotrain-data-lucifer_multi
co2_eq_emissions: 114.27071200298751
---

# Model Trained Using AutoTrain

- Problem type: Multi-class Classification
- Model ID: 844026969
- CO2 Emissions (in grams): 114.27071200298751

## Validation Metrics

- Loss: 0.01150986272841692
- Accuracy: 0.99642966866208
- Macro F1: 0.9962909855453217
- Micro F1: 0.99642966866208
- Weighted F1: 0.9964296206983974
- Macro Precision: 0.9963861124818623
- Micro Precision: 0.99642966866208
- Weighted Precision: 0.9964357526967369
- Macro Recall: 0.9962012842304059
- Micro Recall: 0.99642966866208
- Weighted Recall: 0.99642966866208


## 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/lucifermorninstar011/autotrain-lucifer_multi-844026969
```

Or Python API:

```
from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("lucifermorninstar011/autotrain-lucifer_multi-844026969", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("lucifermorninstar011/autotrain-lucifer_multi-844026969", use_auth_token=True)

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

outputs = model(**inputs)
```