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---
language:
- en
pipeline_tag: text-classification
tags:
- text
- nlp
- correction
---
# Model Trained Using AutoNLP
- Problem type: Multi-class Classification
- Model ID: 492513457
- CO2 Emissions (in grams): 5.527544460835904
## Validation Metrics
- Loss: 0.07609463483095169
- Accuracy: 0.9735624586913417
- Macro F1: 0.9736173135739408
- Micro F1: 0.9735624586913417
- Weighted F1: 0.9736173135739408
- Macro Precision: 0.9737771415197378
- Micro Precision: 0.9735624586913417
- Weighted Precision: 0.9737771415197378
- Macro Recall: 0.9735624586913417
- Micro Recall: 0.9735624586913417
- Weighted Recall: 0.9735624586913417
## 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": "Is this text really worth it?"}' https://api-inference.huggingface.co/models/wajidlinux99/gibberish-text-detector
```
Or Python API:
```
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("wajidlinux99/gibberish-text-detector", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("wajidlinux99/gibberish-text-detector", use_auth_token=True)
inputs = tokenizer("Is this text really worth it?", return_tensors="pt")
outputs = model(**inputs)
```
# Original Repository
***madhurjindal/autonlp-Gibberish-Detector-492513457 |