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---
tags:
- autotrain
- text-classification
language:
- unk
widget:
- text: "I love AutoTrain 🤗"
datasets:
- karalif/autotrain-data-formality6600
co2_eq_emissions:
emissions: 0.010027389793904551
---
# Model Trained Using AutoTrain
- Problem type: Binary Classification
- Model ID: 3757299967
- CO2 Emissions (in grams): 0.0100
## Validation Metrics
- Loss: 0.233
- Accuracy: 0.912
- Precision: 0.906
- Recall: 0.922
- AUC: 0.970
- F1: 0.914
## 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/karalif/autotrain-formality6600-3757299967
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("karalif/autotrain-formality6600-3757299967", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("karalif/autotrain-formality6600-3757299967", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
``` |